HK1207755B - Method and system for online advertising - Google Patents

Description

Method and system for online advertising

background

1. Technical Field

The present teachings relate to methods, systems, and programming for Internet services. In particular, the present teachings relate to methods, systems, and programming for online advertising.

2. Discussion of technical background

Online advertising is a form of promotion that uses the Internet and the World Wide Web to deliver marketing messages in order to attract consumers. Examples of online advertising include contextual advertising on search engine results pages, banner ads, blogs, rich media ads, interstitial ads, online classified ads, ad networks, and email marketing. Many of these types of ads are delivered by ad serving mechanisms such as ad servers.

FIG1 illustrates a prior art system 100 for online advertising. System 100 includes an ad serving mechanism 102 for delivering advertisements from advertisers 104 stored in ad archives 106 to users 108. Display advertisements can appear on user 108's web pages in a variety of formats, including web banners. In FIG1 , a personalized advertising mechanism 110 can be employed in conjunction with ad serving mechanism 102 to provide personalized display advertisements to each individual user 108 based on the user's profile and online behavior. However, prior art system 100 only establishes a one-way communication channel from advertiser 104 to user 108 for delivering marketing messages. Information, such as user feedback on delivered messages, cannot be effectively provided to advertisers 104. Prior art system 100 also lacks an effective means for identifying the most desirable audience for each advertiser 104 from all available users 108 in order to provide targeted advertising. Furthermore, the prior art system 100 applies traditional revenue models such as cost per impression, cost per visitor, cost per click, annual service fee, etc., which lack flexibility, especially in the context of social networking.

Therefore, there exists a need to provide an improved solution and flexible monetization scheme for online advertising through a two-way communication channel between the most relevant entities and targets in order to address the above-mentioned issues.

Overview

The present teachings relate to methods, systems, and programming for online advertising.

In one example, a method for online advertising implemented on at least one machine is disclosed, each machine having at least one processor, storage, and a communication platform connected to a network. Based on a first segment of information associated with each target and a second segment of information associated with an entity, one or more targets associated with the entity are identified. The one or more targets are deemed to be potentially interested in content provided by the entity. A connection is established between the entity and each identified target via a bidirectional communication channel. Activity between the entity and each target via the bidirectional communication channel is monitored. The entity delivers content to the identified target via the bidirectional communication channel established between the entity and the identified target. In response to the delivered content, the identified target can provide feedback to the entity via the bidirectional communication channel.

In another example, a method for online advertising implemented on at least one machine is disclosed, each machine having at least one processor, storage, and a communication platform connected to a network. A first segment of information associated with a user is obtained. One or more entities are identified relative to the user based on the first segment of information associated with the user and second segment of information associated with each entity. Each identified entity is capable of providing content, and the one or more identified entities are considered to potentially have content of interest to the user. A connection is established between the user and each identified entity via a bidirectional communication channel. Based on the first segment of information associated with the user and the second segment of information associated with each identified entity, one or more segments of content that can be provided by each identified entity are identified. Delivery of the identified one or more segments of content from each identified entity is facilitated via the bidirectional communication channel established between each identified entity and the user. The identified entity delivers the identified one or more segments of content to the user via the bidirectional communication channel therebetween. In response to the delivered one or more segments of content, the user is capable of providing feedback to the identified entity via the bidirectional communication channel therebetween.

In yet another example, a method for online advertising implemented on at least one machine, each machine having at least one processor, storage, and a communication platform connected to a network, is disclosed. One or more targets associated with an entity are identified. The one or more targets are deemed to be potentially interested in content provided by the entity. A mechanism for observing communications between each identified target and the entity is automatically established via a bidirectional communication channel established between the entity and each identified target. For each bidirectional communication channel, an amount of content delivered by the entity to the corresponding identified target via the bidirectional communication channel therebetween is monitored. A monetary amount to be charged to the entity is calculated based on the monitored amount of content delivered from the entity to each identified target.

In another example, a method for online advertising implemented on at least one machine is disclosed, each machine having at least one processor, storage, and a communication platform connected to a network. Based on the influence level of each target on a social networking platform, one or more targets associated with an entity are identified. The one or more targets are deemed to be potentially interested in content provided by the entity. A connection is established between the entity and each identified target via a two-way communication channel. Activity between the entity and each identified target via the two-way communication channel is monitored. Information related to the monitored activity is provided to the entity to facilitate the entity's determination whether to send content to each identified target. The entity delivers content to the identified target via the two-way communication channel established between the entity and the identified target. In response to the delivered content, the identified target can provide feedback to the entity via the two-way communication channel.

In another example, a method for online advertising implemented on at least one machine is disclosed, each machine having at least one processor, storage, and a communication platform connected to a network. Based on a first segment of information associated with each target and a second segment of information associated with the entity, one or more targets associated with an entity are identified. The one or more targets are deemed to be likely to be interested in content provided by the entity. The entity is recommended to the one or more identified targets in order to follow the entity. Based on a response to the recommendation, a connection is established between the entity and each identified target via a two-way communication channel on a social networking platform. The entity delivers the content to the identified target via the two-way communication channel established between the entity and the identified target. In response to the delivered content, the identified target can provide feedback to the entity via the two-way communication channel.

In another example, a method for online advertising implemented on at least one machine is disclosed, each machine having at least one processor, storage, and a communication platform connected to a network. Based on a first segment of information associated with each target and a second segment of information associated with the entity, one or more targets associated with an entity are identified. The one or more targets are deemed to be potentially interested in content provided by the entity. The entity is encouraged to send an invitation to follow the entity to the one or more identified targets. Based on responses to the invitation, a connection is established between the entity and each identified target via a two-way communication channel on a social networking platform. The entity delivers the content to the identified target via the two-way communication channel established between the entity and the identified target. In response to the delivered content, the identified target can provide feedback to the entity via the two-way communication channel.

In a different example, a system for online advertising is disclosed. The system includes an identifier, a connection initiator, and an online activity monitor. The identifier is configured to identify one or more targets associated with an entity based on a first segment of information associated with each target and a second segment of information associated with the entity. The one or more targets are considered to be potentially interested in content provided by the entity. The connection initiator is configured to establish a connection between the entity and each identified target via a bidirectional communication channel. The online activity monitor is configured to monitor activity between the entity and each identified target via the bidirectional communication channel. The entity delivers the content to the identified target via the bidirectional communication channel established between the entity and the identified target. In response to the delivered content, each identified target can provide feedback to the entity via the bidirectional communication channel.

Another concept relates to software for online advertising. According to this concept, the software product includes at least one machine-readable non-transitory medium and information carried by the medium. The information carried by the medium can be executable program code data related to parameters associated with a request or operating parameters, such as information related to a user, request, or social group.

In one example, a machine-readable and non-transitory medium has recorded thereon information for online advertising, wherein, when read by the machine, the information causes the machine to perform a series of steps. Based on a first segment of information associated with each target and a second segment of information associated with an entity, one or more targets associated with the entity are identified. The one or more targets are deemed to be potentially interested in content provided by the entity. A connection is established between the entity and each identified target via a bidirectional communication channel. Activity between the entity and each target via the bidirectional communication channel is monitored. The entity delivers the content to the identified target via the bidirectional communication channel established between the entity and the identified target. In response to the delivered content, the identified target can provide feedback to the entity via the bidirectional communication channel.

BRIEF DESCRIPTION OF THE DRAWINGS

The methods, systems, and/or programming described herein are further described according to exemplary embodiments. These exemplary embodiments are described in detail with reference to the accompanying drawings. These embodiments are non-limiting exemplary embodiments, in which like reference numerals represent similar structures throughout the several views of the drawings, and in which:

FIG1 depicts a prior art system for online advertising;

FIG2 is a high-level exemplary system diagram of a system for online advertising according to one embodiment of the present teachings;

FIG3 is another high-level exemplary system diagram of a system for online advertising according to one embodiment of the present teachings;

FIG4 is yet another high-level exemplary system diagram of a system for online advertising according to one embodiment of the present teachings;

FIG5 is a flow chart of an exemplary process of a system for online advertising according to one embodiment of the present teachings;

6 is a flow chart of another exemplary process of a system for online advertising according to one embodiment of the present teachings;

7 is a system diagram of an exemplary advertisement-target identifier of a system for online advertising according to one embodiment of the present teachings;

FIG8 is a flow chart of an exemplary process of an ad-target identifier according to one embodiment of the present teachings;

FIG9 is a system diagram of an exemplary target-ad identifier of a system for online advertising according to one embodiment of the present teachings;

FIG10 is a flow chart of an exemplary process of a target-ad identifier according to one embodiment of the present teachings;

FIG11 is a system diagram of an exemplary connection initiator of a system for online advertising according to one embodiment of the present teachings;

FIG12 is a flow chart of an exemplary process for connecting an initiator according to one embodiment of the present teachings;

FIG13 depicts a bidirectional communication channel established between an entity and a target according to one embodiment of the present teachings;

FIG14 depicts information exchange through a bidirectional communication channel established between an entity and multiple targets on a social networking platform according to one embodiment of the present teachings;

FIG15 depicts information exchange through a bidirectional communication channel established between multiple entities and a target on a social networking platform according to one embodiment of the present teachings;

FIG16 depicts information exchange via a bidirectional communication channel established between an entity and multiple targets according to one embodiment of the present teachings;

FIG17 depicts information exchange via a bidirectional communication channel established between multiple entities and a target according to one embodiment of the present teachings;

FIG18 is a system diagram of an exemplary online activity monitor of a system for online advertising according to one embodiment of the present teachings; and

FIG19 depicts a general computer architecture upon which the present teachings may be implemented.

Detailed description

In the following detailed description, numerous specific details are set forth by way of example in order to provide a thorough understanding of the relevant teachings. However, it will be apparent to one skilled in the art that the present teachings can be practiced without such details. In other instances, well-known methods, processes, systems, components, and/or circuits have been described at a relatively high level, rather than in detail, in order to avoid unnecessarily obscuring aspects of the present teachings.

This disclosure describes methods, systems, and programming aspects for online advertising. The methods and systems disclosed herein enable the establishment of a two-way, real-time communication channel between advertisers and their most desired audiences on social networking platforms. The online advertising mechanism employed in this disclosure is not only display-based but also leverages personalized, two-way communication between advertisers and targets to enhance ad quality, thereby preventing the mass-marketing of identical ads to targets. Compared to traditional display advertising that relies on advanced metadata, the methods and systems disclosed herein enable the presentation of more dynamic, granular, and time-sensitive information about products to targets in real time. Furthermore, the methods and systems provide a personalized platform for ranking advertisers/ads for users and users for advertisers based on profiling of both users and advertisers/ads. Furthermore, based on the information exchanged through the two-way communication channel between advertisers and targets, such as the amount of information, number of audiences, or connections, this disclosure provides a more flexible monetization solution.

Additional advantages and novel features will be set forth in the detailed description which follows, and in part will become apparent to those skilled in the art upon examination of the following description and accompanying drawings, or may be learned by production or operation of the examples. The advantages of the present teachings may be realized and obtained by practice or use of various aspects, means, and combinations of the methods set forth in the detailed examples discussed below.

2 is a high-level diagram of a system for online advertising according to one embodiment of the present teachings. System 200 includes a two-way ad network platform 202, an ad serving mechanism 204, a plurality of ad-related profiles 206, 208, 210, and a plurality of user-related profiles 212, 214, 216. In this example, the two-way ad network platform 202 acts as a two-way communication channel between an entity 218 (e.g., a business entity or advertiser) and a target 220. In this example, the target 220 is a user identified by the two-way ad network platform 202 as a desired audience for the entity 218.

The two-way ad network platform 202 may include a target-ad identifier 222, an ad-target identifier 224, a target-ad archive 226, and an ad-target archive 228. The target-ad identifier 222 is responsible for identifying one or more entities 218 for each target 220 based on information related to the entities 218, such as information stored in the ad archive 206, the promotion archive 208, and the advertiser profile archive 210. The identified entities for each target may be stored in the target-ad archive 226 and retrieved by the ad serving mechanism 204 to deliver corresponding content, such as advertisements or promotional messages, to each target 220. On the other hand, the ad-target identifier 224 is configured to identify one or more targets 220 for each entity 218 based on information related to the targets 220, such as information stored in the target-related content archive 212, the target activity archive 214, and the target profile archive 216. The identified targets for each entity may be stored in the ad-target archive 228. Each entity 218 can then direct targeted advertising to their identified most desirable audiences via the two-way ad network platform 202, for example, by delivering advertising and promotional content to the targets 220. Feedback on the delivered content can be received from one or more targets 220 and provided to the entity 218 via the same two-way ad network platform 202.

FIG3 is another high-level schematic diagram of a system for online advertising according to one embodiment of the present teachings. In this example, system 300 is applicable to any social networking platform, such as, but not limited to, Facebook, Twitter, LinkedIn, Renren, Weibo, QQ, and the like. In addition to the target-ad identifier 222, ad-target identifier 224, target-ad profile 226, and ad-target profile 228 described above in FIG2 , in this example, a two-way advertising network platform 302 also includes a connection initiator 304 and an online activity monitor 306. In this example, connection initiator 304 is configured to establish a connection between entity 218 and target 220 on the social networking platform via a two-way communication channel. In one example, connection initiator 304 may be responsible for creating accounts for entity 218 and/or target 220 on the social networking platform and recommending the entity account to target 220 in order to follow entity 218. Upon accepting the recommendation, entity 218 may deliver content, such as an advertisement or promotional content, to the target account, for example, in the form of a social network message. In response to the delivered content, target 220 may provide feedback to the entity account in the form of a social network message or activity such as a click, comment, like/dislike, or forwarding. In another example, once a target 220 is identified, a list of targets may be provided to entity 218 to determine whether an invitation to follow entity 218 should be sent to the identified target 220. That is, in this example, connection initiator 304 may be responsible for facilitating entity 218 sending an invitation to follow entity 218 to the identified target 220 on the social networking platform. Once the invitation is accepted, entity 218 may deliver content, such as advertising or promotional content, to the target account, for example, in the form of a social network message. In response to the delivered content, target 220 may provide feedback to the entity account in the form of a social network message or activity such as a click, comment, like/dislike, or forwarding.

In this example, the online activity monitor 306 is configured to monitor activity between the entity 218 and the target 220 via the two-way communication channel. Activity includes any online activity performed by the entity 218 or the target 220 on the social networking platform via the two-way communication channel, such as information exchange in the form of social network messages, account creation, connection establishment or termination, or responses to received messages (e.g., clicks, comments, likes/dislikes, forwarding). The monitored activity can be used by the entity 218 to facilitate the entity 218's determination of whether to send content to each identified target 220. The monitored activity can also be used by the two-way advertising network platform 302 to calculate a monetary amount to be charged to the entity 218 according to any suitable monetization scheme based on information related to the monitored activity.

FIG4 is another high-level schematic diagram of a system for online advertising according to one embodiment of the present teachings. In this example, system 400 is similar to system 300 shown in FIG3 , except that the two-way ad network platform 402 in this example also includes an ad serving mechanism 404 as part of the two-way ad network platform 402. Thus, in this example, the display format of the ad content can be different from the display format in system 300, i.e., a social network message. For example, the ad serving mechanism 404 can retrieve ad content from an ad archive 206 or a promotion archive 208 for a specific entity 218 and display the content as a regular display ad on a web page of a social network account of an identified target 220. In this case, the display of the display ad can also be taken into account when calculating the monetary amount to be charged to the entity 218.

FIG5 is a flow chart of an exemplary process for online advertising according to one embodiment of the present teachings. Beginning at block 502, one or more targets are identified for an entity. Each target is considered likely to be interested in content provided by the entity. At block 504, if more than one target has been identified in block 502, the targets are ranked and filtered based on various parameters, such as relevance to the entity, level of influence within the context of a social network, or purchase intent and probability. Moving to block 506, a connection is established between the entity and each identified target via a bidirectional communication channel. At block 508, content, such as an advertisement, is delivered by the entity to each identified target via the bidirectional communication channel. At block 510, a determination is made as to whether the identified target has provided any feedback in response to the delivered content. If so, at block 512, the feedback is delivered to the entity via the bidirectional communication channel. Regardless, at block 514, activity between the entity and each target via the bidirectional communication channel is monitored.

Figure 6 is a flow chart of another exemplary process for online advertising according to one embodiment of the present teachings. Beginning at block 602, one or more entities are identified for a user. Each identified entity is capable of providing content, and one or more of the identified entities are considered likely to have content of interest to the user. At block 604, if more than one entity has been identified in block 602, the entities are ranked and filtered based on various parameters, such as relevance to the user. Moving to block 606, a connection is established between the user and each identified entity via a bidirectional communication channel. At block 608, each identified entity delivers content, such as an advertisement, to the user via the bidirectional communication channel. At block 610, a determination is made as to whether the user has provided any feedback in response to the delivered content. If so, at block 612, the feedback is delivered to the entity via the bidirectional communication channel. However, at block 614, activity between the user and each identified entity via the bidirectional communication channel is monitored. Optionally, one or more pieces of content that may be provided by each identified entity may be identified and ranked based on various parameters, such as relevance to the user and the effectiveness of the entity delivering each piece of content.

It should be understood that although Figures 5 and 6 relate to aspects of identifying and ranking targets for entities and identifying and ranking entities for users, respectively, the processes in Figures 5 and 6 can be combined in other examples. That is, based on user social and behavioral analysis and mining, the most relevant and influential users for each entity can be identified first. Given that the identified users (targets) may be interested in multiple entities/ads, entities/ads can also be identified and ranked relative to specific targets in the same process.

FIG7 is a system diagram of an exemplary ad-target identifier for a system for online advertising according to one embodiment of the present teachings. Ad-target identifier 224 includes a target information extractor 702, a target characterization module 704, an ad information extractor 706, an ad characterization module 708, and an ad-target relevance analyzer 710. In this example, target information extractor 702 is responsible for extracting information related to each target from various target-related information archives. The target-related information archives include, for example, a target profile archive 216 storing information reflecting each target's profile (e.g., gender, age, location, occupation, etc.), a target activity archive 214 storing information about each target's online activities (e.g., browsing behavior, actions in a social networking environment, etc.), a target-related content archive 212 storing information about content related to each target (e.g., articles, text, video, and audio created or consumed by each target), and an influence target archive 712 storing information related to each target's level of social influence. It should be understood that any other suitable target-related information archives may also be included. For example, an information archive storing information reflecting each target's purchase behavior (e.g., online purchase history data) can be used to provide purchase behavior information to the target information extractor 702. The target characterization module 704 is configured to characterize each target based on the corresponding target-related information extracted from various information archives to create multiple target vectors. The target vectors include, for example, a category vector, a keyword vector, or a latent variable vector reflecting the interests of each target.

Similarly, the ad information extractor 706 is configured to extract entity-related information from various entity-related information archives. In this example, the advertiser profile archive 210 may include information reflecting the profile of each entity (e.g., location, product, etc.); the ad archive 206 and the promotion archive 208 may include information about each piece of content to be delivered by the entity (e.g., product promotions, new model releases, celebrity endorsements, etc.). It should be understood that some of the entity-related information can be obtained through the metadata of the content to be delivered by the entity, and the ad metadata enhancement module 714 can be applied to obtain more entity-related information through metadata enhancement and enrichment. However, all obtained entity-related information is input into the ad characterization module 708 to create an entity vector by characterizing the relevant information of each entity. In this example, the entity vector includes, for example, a category vector, a keyword vector, or a latent variable vector to reflect the interests of each entity. It should be understood that for each piece of content, such as an advertisement to be delivered by an advertiser, a content vector can also be created to reflect the theme of each piece of content. In other words, entity-related information can be characterized at both the entity level and the content level. For example, each advertiser can be characterized to depict its interests, while each of the advertiser's ads can also be characterized to specify a fine-grained theme. In one example, an advertiser can be characterized under the category of "cars," and ads provided by that advertiser can also be characterized under various categories, such as "trucks," "sports cars," "hybrid cars," "Toyota," and so on.

In this example, ad-target relevance analyzer 710 is configured to analyze the relevance between each entity and target pair based on relevance model 716 to generate an ad-target relevance score 718 for each entity and target pair. In this example, relevance model 716 can be any suitable machine-learned matching function between a target vector and an entity vector. For a given entity, such as an advertiser or an ad, a relevance score 718 for the target is obtained by applying the machine-learned matching function.

In this example, the ad-targeting identifier 224 also includes a target influence analyzer 720 for calculating a target influence score 726 based on information related to each target's level of social influence. The target influence analyzer 720 may include a link analysis module 722 configured to apply link analysis, such as PageRank or any suitable web link-based ranking algorithm, to the social network based on the target's social connections. Each target's influence score 726 may be influenced by its PageRank calculated by the link analysis module 722. The target influence analyzer 720 may also include a topical link analysis module 724 configured to apply a topical link propagation algorithm, such as topical PageRank, to the social network. Before applying the topical link propagation algorithm, one or more high-influence targets may first be identified as tagged seeds on the social network platform. High-influence targets may be celebrities on the social network who have been manually categorized into predetermined categories/topics. Celebrities may be automatically identified, for example, by the number of followers on the social network platform, or they may be manually verified. Followers of high-influence targets in the social network are considered targets that are influenced by the identified high-influence target and may have the same topics of interest as the high-influence target. In this example, the results from both the link analysis module 722 and the thematic link analysis module 724 for a given target are combined into a target influence score 726, which is independent of any entity.

In this example, the ad-target identifier 224 also includes a target purchase analyzer 728, which is responsible for calculating a target purchase score 730 reflecting the purchase intent and probability of each target based on, for example, the target's online purchase history and patterns. Because purchase intent and probability are important to the effectiveness of online advertising, in this example, the target purchase score 730 can be considered a boost factor and provided, along with the ad-target relevance score 718 and the target influence score 726, to the target ranking module 732 and the target filtering module 734. In this example, for each entity-target pair, different scores can be combined with equal or different weights. The combined scores are applied by the target ranking module 732 to rank all available targets for a given advertiser or ad. The target filtering module 734 can apply different rules to filter out certain targets. In one example, each entity can specify or enforce a maximum number N of targets they are interested in, so that only the top N ranked targets are retained after filtering. In another example, the target filtering module 734 can exclude targets that have already voluntarily followed the entity on any social networking platform. The ad-target indexer 736 may be responsible for indexing each entity's identified targets and storing the index in the ad-target archive 228 .

Figure 8 is a flow chart of an exemplary process for an ad-target identifier according to one embodiment of the present teachings. Beginning at block 802, information related to targets is extracted. This information includes, for example, information reflecting each target's profile, information regarding each target's online activities, information regarding content related to each target, information regarding each target's social influence level, and information reflecting each target's purchasing behavior. At block 804, each target is characterized based on the corresponding extracted information to create a target vector. At block 806, information related to each advertiser or ad is extracted, such as information reflecting the advertiser's profile, information regarding each ad, and information regarding the advertiser's effectiveness in delivering each ad. At block 808, each advertiser or ad is characterized based on the corresponding extracted information to create an entity or content vector. Moving to block 810, the target vector and the entity or content vector are used to calculate an ad-target relevance score based on, for example, any machine learning matching function. At block 812, a target influence score is also calculated based on each target's social influence level. At block 814, a target purchase score is calculated based on each target's purchasing behavior as a reinforcement factor. Continuing with block 816, for each advertiser or ad, all available targets are ranked based on a score that combines the ad-target relevance score, the target influence score, and the target purchase score. At block 818, some targets may be excluded from consideration, leaving the remaining targets as identified targets for each advertiser or ad. Finally, at block 820, the identified targets for each advertiser or ad are indexed.

FIG9 is a system diagram of an exemplary target-ad identifier for a system for online advertising according to one embodiment of the present teachings. Components already described above in FIG7 will not be described again. In this example, target-ad identifier 222 also includes an ad effectiveness evaluator 902, which is configured to calculate ad effectiveness scores 904 for all entities, such as advertisers, and their ads based on their online activity monitored by online activity monitor 306, according to an activity evaluation model 906. For example, activity evaluation model 906 can be any suitable statistical machine learning model. In one example, where the acceptance of a connection request from an entity corresponds to a click (and therefore is a positive example), various web search click modeling techniques can be applied. As described above, an ad-target relevance score 718 can also be calculated for each entity-target pair by ad-target relevance analyzer 710. Ad effectiveness score 904 and relevance score 718 are combined and provided to ad ranking module 908 and ad filtering module 910 to identify one or more entities (e.g., advertisers) or ads for each target (user). It should be noted that in a second-price auction model, the ranking and filtering of advertisers or ads may also be affected by the winning bid rate (cost per byte per follower at a certain position). The second price may be charged to the entity as part of the monetization scheme. The target-ad indexer 912 may be responsible for indexing the identified advertisers or ads for each user and storing the index in the target-ad archive 226.

Figure 10 is a flow chart of an exemplary process for a target-ad identifier according to one embodiment of the present teachings. Beginning at block 802, information related to the targets is extracted. This information includes, for example, information reflecting the profile of each target, information about each target's online activity, information about content related to each target, information related to each target's level of social influence, and information reflecting each target's purchasing behavior. At block 804, each target is characterized based on the corresponding extracted information to create a target vector. At block 806, information related to each advertiser or ad is extracted, such as information reflecting the advertiser's profile, information about each ad, and information about the advertiser's effectiveness in delivering each ad. At block 808, each advertiser or ad is characterized based on the corresponding extracted information to create an entity or content vector. Moving to block 810, an ad-target relevance score is calculated using the target vector and the entity or content vector, based on, for example, any machine learning matching function. At block 1002, online activity between the entity and the target is monitored to reflect the effectiveness of delivering content (e.g., ads) to the user. At block 1004, an effectiveness score is calculated based on the monitored activity, for example, according to any suitable web search click model. Proceeding to block 1006, for each user, all available advertisers or ads are ranked based on a score that combines the ad-target relevance score and the ad effectiveness score. At block 1008, some advertisers or ads may be excluded from consideration, leaving the remaining advertisers or ads as identified advertisers or ads for each user. Finally, at block 1010, the identified advertisers or ads for each user are indexed.

FIG11 is a system diagram of an exemplary connection initiator for an online advertising system according to one embodiment of the present teachings. The connection initiator 304 includes an advertiser registration unit 1102, an advertiser-target connector 1104, a connection recommendation unit 1106, a recommendation feedback unit 1108, and a connection control unit 1110. Advertiser registration unit 1102 is configured to, in response to a request, create an advertiser account 1112 for each advertiser on the social networking platform based on the advertiser's profile retrieved from advertiser profile archive 210. Different account types 1114 can be assigned to advertiser accounts 1112, and these different account types 1114 can affect the relationship between advertisers and identified targets on the social networking platform. Advertiser-target connector 1104 is responsible for establishing a bidirectional communication channel between advertiser accounts 1112 and target accounts 1116 on the social networking platform. In this example, based on an index stored in the ad-target archive 228, connection recommendation unit 1106 can recommend advertiser accounts 1112 to corresponding identified targets for attention. In response to the recommendation, the target account 1116 can accept, reject, or ignore the recommendation through the recommendation feedback unit 1108. The result is then provided to the advertiser-target connector 1104 to determine whether a two-way communication channel can be established and what type of relationship exists between the advertiser account 1112 and the corresponding target account 1116. In one example, a persistent/premium relationship does not expire as long as the target does not explicitly disable the connection. In another example, a temporary/short-term relationship can be established so that the connection is valid during a specified period of time, such as within a seasonal advertising campaign. In yet another example, an implicit relationship means that the target does not explicitly accept the recommendation for attention. In this example, the connection between each advertiser account 1112 and the corresponding target account 1116 can be maintained and controlled by the connection control unit 1110. For example, for any communication channel built based on a temporary/short-term relationship, the connection control unit 1110 can terminate the connection once the specified period of time ends. It should be understood that although Figure 11 describes the connection initiator 304 from the entity's (advertiser's) perspective, the same mechanism can be used to create a target account 1116 for a user and recommend the target account 1116 to the advertiser account 1102 for attention, i.e., in reverse.

FIG12 is a flow chart of an exemplary process of a connection initiator according to one embodiment of the present teachings. Beginning at block 1202, an account is created for each advertiser on the social networking platform. At block 1204, for each identified target, a corresponding advertiser account is recommended for the target to follow. At block 1206, if the target does not accept recommendations for a particular advertiser account, then at block 1208, an implicit connection is established between the target account and the advertiser account. If the target accepts the follow recommendation at block 1206, an explicit connection is established at block 1210. At block 1212, a determination is made as to whether the advertiser account is of a temporary/short-term type. If so, at block 1214, the connection between the temporary/short-term advertiser account and the target account is terminated upon account expiration. Otherwise, if the advertiser account is of a persistent/premium type, then at block 1216, the explicit connection between the persistent/premium advertiser account and the target account is maintained unless the target account explicitly terminates the connection.

FIG13 illustrates a bidirectional communication channel established between an entity and a target according to one embodiment of the present teachings. Once a connection initiator 304 establishes a direct connection between an entity and a corresponding target on a social networking platform, a bidirectional real-time communication channel becomes available for each pair of entities and targets to exchange information directly. For example, advertisers can broadcast content such as product promotions, new model releases, and celebrity endorsements to their followers (identified users) in the form of social networking messages. Simultaneously, identified users can provide timely and direct feedback to the advertiser or forward and comment on messages to their friends. Once a connection is established on a social networking platform, communication becomes bidirectional, and users can provide their feedback via the same channel. As shown in FIG13 , an online activity monitor 306 of the system 300, 400 monitors all activity between advertisers and users via the bidirectional communication channel, and information related to the monitored activity can be used to determine the monetary amount to be charged to the advertiser.

It should be understood that the connection between advertisers and users can be symmetric or asymmetric. As described above, for a given entity (advertiser) "A", the system 300, 400 can identify one or more corresponding targets (users) "a", "b", ... "n". On the other hand, for a given target "a", the system 300, 400 can also identify one or more corresponding entities. If entity "A" is also identified as one of the corresponding entities of target "a", then the connection between entity "A" and target "a" is symmetric. If entity "A" is not identified as one of the corresponding entities of target "a", then the connection is asymmetric. For example, because of a celebrity's high social influence and purchase intention for cars, the system 300, 400 can identify the celebrity as one of the most desired audiences for advertisers of economy cars. However, when the system 300, 400 identifies potential entities such as car manufacturers, dealers, and advertisers of cars, advertisers of economy cars may not be on the list of identified entities for the celebrity. In this case, the connection is asymmetric in the sense that the target is recommended to the entity but the entity is not recommended to the same target. In one example, the system 300, 400 can limit the validity of only symmetric connections. In other examples, the system 300, 400 can also retain asymmetric connections and apply different monetization schemes to symmetric and asymmetric connections. For example, advertisers can be charged a higher rate for symmetric connections than for asymmetric connections.

FIG14 illustrates an exchange of information over a bidirectional communication channel established between an entity and multiple targets on a social networking platform, according to one embodiment of the present teachings. In this example, multiple targets are identified for an advertiser, and a bidirectional communication channel is established between advertiser account 1112 and target accounts 1116. Advertiser account 1112 on the social networking platform may include a social network message broadcast unit 1402 and a feedback output 1404. Social network message broadcast unit 1402 may be any suitable mechanism for broadcasting a message to its followers on the social networking platform, such as a status update, post, forward, private message, etc. The message is broadcast to all identified targets based on an index in ad-target archive 228, and the message content is retrieved from available archives, such as ad archive 206 or promotion archive 208. Each target account 1116 includes a social network message output 1406 for presenting messages received from advertiser account 1112 in the account's regular message display section or in a separate "Sponsored" section. Each target account 1116 may also include a feedback input 1408 for providing feedback in response to a received message. Feedback includes, for example, clicks, comments, reposts, thumbs-up/down votes, etc. Feedback is sent to the advertiser account 1112 via a two-way communication channel.

FIG15 illustrates an exchange of information over a bidirectional communication channel established between multiple entities and a target on a social networking platform according to one embodiment of the present teachings. In this example, multiple entities (advertisers) are identified for a target (user), and a bidirectional communication channel is established between advertiser account 1112 and target account 1116. Unlike FIG14 , an index stored in target-ad profile 226 rather than ad-target profile 228 is used by social network message broadcast unit 1402 of the identified advertiser account 1112 to determine the target account 1116 to which to send the message.

FIG16 depicts an exchange of information over a bidirectional communication channel established between an entity and multiple targets according to one embodiment of the present teachings. Unlike FIG14 , display advertising, rather than social network messaging, is used to broadcast content to the targets. In this example, the ad serving mechanism 404 is configured to retrieve content from the ad archive 206 and/or promotion archive 208 for each advertiser account 1112 and send the content to a target account 1116 identified by an index stored in the ad-target archive 228. In the social network context, the display ad output 1602 of each target account 1116 presents a conventional display ad with a dynamic meta content collection as the most recent ad message.

FIG17 illustrates information exchange over a bidirectional communication channel established between multiple entities and a target according to one embodiment of the present teachings. In this example, multiple entities (advertisers) are identified for a target (user), and a bidirectional communication channel is established between advertiser account 1112 and target account 1116. Unlike FIG16 , an index stored in target-ad profile 226 rather than ad-target profile 228 is used by the ad serving mechanism 404 to determine, for each advertiser account 1112, the corresponding target account 1116 in which to serve display ads.

Figure 18 is a system diagram of an exemplary online activity monitor for a system for online advertising according to one embodiment of the present teachings. The online activity monitor 306 may include a rate evaluator 1802, which is configured to calculate a monetary amount to be charged to each entity based on information related to monitored activity between the advertiser account 1112 and the target account 1116 via a bidirectional communication channel. Information may be collected by various devices including a traffic monitor 1804, an ad type analyzer 1806, an agility evaluator 1808, a response monitor 1810, and a distribution monitor 1812. In one example, the monetary amount may be determined based on the product of the amount of content delivered from the advertiser account 1112, the number of followers (target account 1116), and the rate (cost per byte per follower at a location). The amount of content may be monitored by the traffic monitor 1804. The number of followers may be monitored by the distribution monitor 1812. As for the rate, it may be determined based on a display advertising auction/price bidding model during the connection initiation phase. For example, when multiple advertisers or advertisements are provided to a user, the ranking (position) of each advertiser or advertisement on the recommendation list may affect the rate.

In another example, instead of applying an auction/price bidding model to determine the rate, the rate can be determined based on the type of connection relationship. Persistent/high-quality relationships have the highest rate; temporary/short-term relationships have medium rates, and implicit relationships have the lowest rate. The rate can also be determined based on the strength of the connection, which is determined by the combined score in Figures 7 and 9, the quality/authority of the advertiser or ad, the agility determined by the agility evaluator 1808 (how promptly users receive the broadcast content), the type of content being broadcast (e.g., text, rich media, etc.) obtained by the ad type analyzer 1806, and the feedback on the delivered content (e.g., positive, negative, neutral) collected by the response monitor 1810. In another example, each message can contain a tiny URL, so that advertisers can be charged based on a click-through rate similar to a cost-per-click model. As previously described, advertisements can be delivered in the form of display ads rather than social network messages. In this case, the monetary amount can also depend on the impression.

It should be understood that broadcasting can be cross-platform, meaning that once a connection is established, a user can receive advertising messages from any third-party social media product. For example, a user can log in to the system 300, 400 using the user ID of any third-party social media product or directly log in to the third-party social media product. In this case, the revenue generated by charging advertisers can be shared with the third-party social media product provider.

To implement the present teachings, a computer hardware platform may be used as the hardware platform for one or more of the elements described herein. The hardware elements, operating systems, and programming languages of such computers are conventional in nature, and it is assumed that those skilled in the art are sufficiently familiar with them so that those technologies are suitable for substantially implementing the DCP processing described herein. A computer with user interface elements may be used to implement a personal computer (PC) or other type of workstation or terminal device, but if appropriately programmed, the computer may also act as a server. It is believed that those skilled in the art are familiar with the structure, programming, and general operation of such computer equipment, and the resulting figures should be self-explanatory.

FIG19 depicts a general computer architecture on which the present teachings may be implemented, including a functional block diagram illustrating a computer hardware platform including user interface elements. The computer may be a general-purpose computer or a special-purpose computer. This computer 1900 may be used to implement any component of the online advertising architecture described herein. The various components of systems 200, 300, and 400 may all be implemented on one or more computers, such as computer 1900, via hardware, software programs, firmware, or a combination thereof. Although only one such computer is shown for convenience, computer functions related to online advertising may be implemented in a distributed manner across multiple similar platforms to distribute the processing load.

For example, the computer 1900 includes a communication port 1902 that is connected to and from a network connected thereto to facilitate data communication. The computer 1900 also includes a central processing unit (CPU) 1904 in the form of one or more processors for executing program instructions. The exemplary computer platform includes an internal communication bus 1906, various forms of program storage and data storage, such as disks 1908, read-only memory (ROM) 1910, or random access memory (RAM) 1912, various data files for processing and/or communication by the computer, and possibly program instructions to be executed by the CPU 1904. The computer 1900 also includes an I/O component 1914 that supports input/output flows between the computer 1900 and other components therein, such as user interface elements 1916. The computer 1900 may also receive programming and data via network communications.

Thus, various aspects of the online advertising method outlined above can be embodied in programming. The various programmatic aspects of the present technology can be considered to be "products" or "articles of manufacture" typically in the form of executable code and/or associated data carried or embodied in a type of machine-readable medium. Tangible, non-transitory "storage" type media include any or all of the memory or other storage for a computer, processor, or the like, or its associated modules, such as various semiconductor memories, tape drives, disk drives, etc., which can provide storage for software programming at any time.

Sometimes all or part of the software can be transmitted over a network such as the Internet or various other telecommunication networks. For example, such communications can allow the software to be loaded from one computer or processor to another. Thus, another type of medium that can carry elements of the software includes optical, electrical, and electromagnetic waves used, for example, across physical interfaces between local devices via wired and optical landline networks and various air links. Physical elements that carry such waves, such as wired or wireless links, optical links, etc., can also be considered as media that carry the software. As used herein, unless limited to tangible "storage" media, terms such as computer or machine "readable medium" refer to any medium that participates in providing instructions to a processor for execution.

Thus, a machine-readable medium can take a variety of forms, including but not limited to tangible storage media, carrier media, or physical transmission media. Non-volatile storage media include, for example, optical or magnetic disks, such as any storage device or the like in any computer that can be used to implement the system shown in the accompanying drawings or any component thereof. Volatile storage media include dynamic memory, such as the main memory of such a computer platform. Tangible transmission media include coaxial cables; copper cables and optical fibers, including the lines that form a bus within a computer system. Carrier transmission media can take the form of electrical or electromagnetic signals, or sound or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Thus, common forms of computer-readable media include, for example: a floppy disk, a flexible disk, a hard disk, magnetic tape, any other magnetic medium, a CD-ROM, a DVD or DVD-ROM, any other optical medium, punched card stock tape, any other physical storage medium with a pattern of holes, RAM, PROM and EPROM, flash EPROM, any other memory chip or cartridge, a carrier wave that transmits data or instructions, a cable or link that transmits such a carrier wave, or any other medium from which a computer can read programming code and/or data. Many of these forms of computer readable media may be involved in carrying one or more sequences of one or more instructions for execution by a processor.

Those skilled in the art will recognize that the present teachings are applicable to various modifications and/or enhancements. For example, while the implementation of the various components described above may be embodied in hardware devices, it may also be implemented as a software-only solution. Additionally, the components of the systems disclosed herein may be implemented as firmware, a firmware/software combination, a firmware/hardware combination, or a hardware/firmware/software combination.

Although what is considered to be the best mode and/or other examples have been described above, it should be understood that various modifications may be made therein, and the subject matter disclosed herein may be implemented in a variety of forms and examples, and the present teachings may be applied in a variety of applications, only some of which are described herein. It is intended that any and all applications, modifications, and variations that fall within the true scope of the present teachings be claimed by the following claims.

Claims (52)

1. A method for online advertising implemented on at least one machine, each machine having at least one processor, storage, and a communication platform connected to a network, the method comprising: Based on information from a first fragment associated with each of the one or more targets and information from a second fragment associated with the entity, one or more targets associated with the entity are identified, wherein the one or more targets are considered to be potentially interested in a first type of content provided by the entity; A connection is established between the entity and each target via a two-way communication channel, wherein the connection is either a first-type connection or a second-type connection based on a recommendation relationship between the entity and each target; and Monitoring activities between the entity and each target via the bidirectional communication channel, wherein the entity delivers the first content to the first target of the one or more targets via the bidirectional communication channel established between the entity and the first target; and In response to the first content being delivered, the first target is able to provide feedback to the entity via the bidirectional communication channel. 2. The method of claim 1, wherein the information of the first segment associated with each target includes at least one of the following: The first piece of information in the brief profile reflecting each objective; Second information about the online activities for each objective; Third information regarding the second content related to each objective; The fourth piece of information related to the level of social impact of each objective; and The fifth piece of information reflecting the purchasing behavior of each target. 3. The method of claim 1, wherein the information of the second fragment associated with the entity includes at least one of the following: The first piece of information reflecting the profile of the entity; Second information regarding the second content of each segment to be delivered by the entity; and Third information regarding the validity of the second content delivered by the entity for each segment. 4. The method as described in claim 1, wherein the bidirectional communication channel is located on a social network platform. 5. The method as described in claim 4, wherein establishing the connection comprises: Create the first account for the entity on the social networking platform; Provide the entity's first account to the one or more targets for attention; and Based on the response to the recommendation made by each target, the recommendation relationship between the first account of the entity and the second account of each of the one or more targets is determined. 6. The method of claim 5, wherein the relationship includes at least one of the following: The persistent relationship when the second target of one or more targets receives the attention recommendation; Temporary relationships when a third target of one or more targets accepts the recommended attention and when the connection is terminated after a certain period of time; and Implicit relationship when the fourth objective of one or more objectives does not accept the attention recommendation. 7. The method of claim 5, further comprising: The first content is sent in the form of a message from the first account of the entity to the second account of each of the one or more targets; and The first content is presented to the one or more targets in the form of a message. 8. The method of claim 7, further comprising: Receive input associated with feedback based on a first content from one of the one or more targets; and The feedback is presented to the entity. 9. The method of claim 8, wherein the feedback comprises at least one of the following: Click on the message; The message mentioned in the comments; The message mentioned in the like/dislike comments; and Forward the message. 10. The method of claim 5, further comprising: Sending the first content from an advertising archive associated with the entity to a second account of each of the one or more targets in the form of a display advertisement; and The first content is presented to the one or more targets in the form of a display advertisement. 11. The method of claim 1, further comprising calculating a monetary amount to be charged to the entity based on information related to the activity. 12. The method of claim 11, wherein the information related to the activity includes at least one of the following: The type of the first content to be delivered by the entity; The agility of the first content delivered by the entity; Traffic volume through the bidirectional communication channel; In response to receiving feedback of the first content; and The distribution of the one or more targets. 13. The method of claim 1, further comprising providing information related to the activity to the entity to facilitate the entity's determination of whether to send the first content to each target. 14. The method of claim 1, wherein identifying the one or more targets comprises: Extract information from the first segment associated with each target; Each target is characterized based on the information in the first segment in order to create multiple target vectors; Extract information about the second fragment related to the entity; The entity is characterized based on the information from the second fragment in order to create an entity vector; and Based on a corresponding target vector and an entity vector from the plurality of target vectors, a correlation score is calculated for each target and the entity. 15. The method of claim 14, further comprising: Calculate the influence score and purchase score for each target based on the information from the first segment; and The entity's one or more objectives are ranked based on the relevance score, the influence score, and the purchase score. 16. A system for online advertising, comprising: An identifier is configured to identify the one or more targets associated with the entity based on information of a first fragment associated with each of the one or more targets and information of a second fragment associated with the entity, wherein the one or more targets are considered to be potentially interested in a first type of content provided by the entity; A connection initiator, configured to establish a connection between the entity and each target via a bidirectional communication channel, the connection being either a first-type connection or a second-type connection based on a recommended relationship between the entity and each target; and An online activity monitor is configured to monitor activity between the entity and each of the one or more targets via the bidirectional communication channel, wherein... The entity delivers the first content to the first target via the bidirectional communication channel established between the entity and the first target of the one or more targets; and In response to the first content being delivered, the first target is able to provide feedback to the entity via the bidirectional communication channel. 17. The system of claim 16, wherein the connection initiator is further configured to: Create the first account for the entity on the social networking platform; Provide the entity's first account to each of the one or more targets for attention; and Based on the response to the recommendation made by each target, the recommendation relationship between the first account of the entity and the second account of each of the one or more targets is determined. 18. The system of claim 17, wherein the relationship includes at least one of the following: The persistent relationship when the second target of one or more targets receives the attention recommendation; Temporary relationships when a third target of one or more targets accepts the recommended attention and when the connection is terminated after a certain period of time; and Implicit relationship when the fourth objective of one or more objectives does not accept the attention recommendation. 19. The system of claim 17, further comprising: A message broadcasting unit, configured to send the first content in the form of a message from a first account of the entity to a second account of each of the one or more targets; and Message output, configured to present the first content to the one or more targets in the form of a message. 20. The system of claim 19, further comprising: Feedback input, configured to receive input associated with content-based feedback from one of the one or more targets; and Feedback output, which is configured to present the feedback to the entity. 21. The system of claim 16, further comprising a fee estimator configured to calculate a monetary amount to be charged to the entity based on information relating to the activity. 22. The system of claim 16, wherein the identifier is further configured to: Extract information from the first segment associated with each target; Each target is characterized based on the information in the first segment in order to create multiple target vectors; Extract information about the second fragment related to the entity; The entity is characterized based on the information from the second fragment in order to create an entity vector; and Based on the corresponding target vectors and entity vectors of the multiple targets, a correlation score is calculated for each target and the entity. 23. The system of claim 22, wherein the identifier is further configured to: Based on the information from the first segment, calculate the influence score and purchase score for each target; and The entity's one or more objectives are ranked based on the relevance score, the influence score, and the purchase score. 24. A machine-readable tangible and non-transitory medium having information thereon recorded for online advertising, characterized in that, when the information is read by the machine, it causes the machine to perform the following: Based on information from a first fragment associated with each of the one or more targets and information from a second fragment associated with the entity, the one or more targets associated with the entity are identified, wherein the one or more targets are considered to be potentially interested in a first type of content provided by the entity; A connection is established between the entity and each target via a two-way communication channel, wherein the connection is either a first-type connection or a second-type connection based on a recommendation relationship between the entity and each target; and Monitoring activities between the entity and each target via the bidirectional communication channel, wherein the entity delivers the first content to the first target of the one or more targets via the bidirectional communication channel established between the entity and the first target; and In response to the first content being delivered, the first target is able to provide feedback to the entity via the bidirectional communication channel. 25. The medium as described in claim 24, wherein the bidirectional communication channel is located on a social networking platform. 26. The medium as claimed in claim 25, characterized in that, corresponding to the information establishing the connection, when read by the machine, it further causes the machine to perform the following: Create the first account for the entity on the social networking platform; Provide the entity's first account to the one or more targets for attention; and Based on the response to the recommendation made by each target, the recommendation relationship between the first account of the entity and the second account of each of the one or more targets is determined. 27. The medium as claimed in claim 26, wherein the relationship comprises at least one of the following: The persistent relationship when the second target of one or more targets receives the attention recommendation; Temporary relationships when a third target of one or more targets accepts the recommended attention and when the connection is terminated after a certain period of time; and Implicit relationship when the fourth objective of one or more objectives does not accept the attention recommendation. 28. The medium as claimed in claim 26, wherein the information, when read by the machine, further causes the machine to perform the following: The first content is sent in the form of a message from the first account of the entity to the second account of each of the one or more targets; and The first content is presented to the one or more targets in the form of a message. 29. The medium as claimed in claim 28, wherein the information, when read by the machine, further causes the machine to perform the following: Receive input associated with feedback based on the content from one of the one or more targets; and The feedback is presented to the entity. 30. The medium as claimed in claim 24, wherein the information, when read by the machine, further causes the machine to perform the following: The monetary amount to be charged to the entity is calculated based on information associated with the activity. 31. The medium as claimed in claim 24, characterized in that, when the information corresponding to identifying the one or more targets is read by the machine, it further causes the machine to perform the following: Extract information from the first segment associated with each target; Each target is characterized based on the information in the first segment in order to create multiple target vectors; Extract information about the second fragment related to the entity; The entity is characterized based on the information from the second fragment in order to create an entity vector; and Based on the corresponding target vectors and entity vectors of the multiple targets, a correlation score is calculated for each target and the entity. 32. The medium as claimed in claim 31, wherein the information, when read by the machine, further causes the machine to perform the following: Based on the information from the first segment, calculate the influence score and purchase score for each target; and The entity's one or more objectives are ranked based on the relevance score, the influence score, and the purchase score. 33. A method for online advertising implemented on at least one machine, each machine having at least one processor, storage, and a communication platform connected to a network, the method comprising: Obtain the first piece of information relevant to the user; Relative to the user, based on information from the first fragment associated with the user and information from the second fragment associated with each entity, one or more entities are identified, each of the one or more entities being able to provide first content, wherein the one or more entities are considered to potentially possess second content of interest to the user; A connection is established between the user and each entity through a two-way communication channel, and the connection is either a first type connection or a second type connection based on the recommendation relationship between the user and each target. Based on the information of the first segment associated with the user and the information of the second segment associated with each entity, a third piece of content is identified that can be provided by each entity, consisting of one or more segments; and The bidirectional communication channel established between each entity and the user facilitates the delivery of third content from each entity, including one or more fragments. Each entity delivers the third content of one or more segments to the user via the bidirectional communication channel; and In response to the third content of the one or more fragments delivered, the user is able to provide feedback to each entity via the bidirectional communication channel. 34. The method of claim 33, wherein the information of the first segment associated with the user includes at least one of the following: The first piece of information reflecting the user's profile; Second information regarding the user's online activities; and The third piece of information concerning the fourth content related to the user. 35. The method of claim 33, wherein the information of the second segment associated with each entity includes at least one of the following: The first piece of information in the profile that reflects each entity; Second information regarding the content of each segment of the third content that can be provided by each entity; and Third information regarding the validity of the third content delivered by each entity for each segment. 36. The method of claim 33, wherein identifying one or more entities comprises: The user is characterized based on the information in the first segment in order to create a user vector; Extract the information of the second fragment associated with each entity; Each entity is characterized based on the information from the second fragment, in order to create multiple entity vectors; and Based on the user vector and a corresponding entity vector of the plurality of entity vectors, a relevance score is calculated between the user and each entity. 37. The method of claim 36, wherein the third content identifying one or more fragments comprises: Based on the information representation of the second fragment, the third content of each fragment of the one or more fragments provided by each entity can be used to create multiple content vectors; and Based on the user vector and a corresponding content vector from the plurality of content vectors, a relevance score is calculated between the user and the content of each segment. 38. The method of claim 37, further comprising: Based on the information from the second segment, calculate the validity score of the third content for each segment; and The third content of the one or more segments is ranked based on the relevance score and the validity score. 39. A method for online advertising implemented on at least one machine, each machine having at least one processor, storage, and a communication platform connected to a network, the method comprising: Identify one or more targets associated with an entity, wherein the one or more targets are considered to be potentially interested in first content provided by the entity; A mechanism is automatically established to observe at least a first communication between each of the one or more targets and the entity via a bidirectional communication channel established between the entity and each target, the bidirectional communication channel being either a first-type channel or a second-type channel based on a recommendation relationship between the entity and each target; For each bidirectional communication channel, monitor the amount of second content delivered by the bidirectional communication channel established between the entity and the corresponding target to the corresponding target of the one or more targets; and The monetary amount to be charged to the entity is calculated based on the amount of second content delivered from the entity to each target. 40. The method of claim 39, wherein the monetary amount is also calculated based on at least one of the following: The type of the second content delivered from the entity to each target; Agility in delivering the second content from the entity to each target; The feedback provided to the entity by each target in response to the delivered second content; and The distribution of one or more targets. 41. The method of claim 39, further comprising: Create the first account for the entity on the social networking platform; Provides the option to recommend the entity's first account to the one or more targets for attention; and Based on the response to the recommendations made by each target, the recommendation relationship between the first account of the entity and the second account of each target is determined. 42. The method of claim 41, wherein the monetary amount is calculated based on information related to the first account of the entity being recommended to the one or more targets for attention. 43. The method of claim 41, wherein the monetary amount is calculated based on the relationship between the first account of the entity and the second account of each target. 44. A method for online advertising implemented on at least one machine, each machine having at least one processor, storage, and a communication platform connected to a network, the method comprising: Based on the influence level of each of the one or more objectives, identify the one or more objectives associated with an entity, wherein the one or more objectives are considered to be potentially interested in the first content provided by the entity; A connection is established between the entity and each target through a two-way communication channel, and the connection is either a first type connection or a second type connection based on the recommendation relationship between the entity and each target. Monitoring activities between the entity and each target via the bidirectional communication channel; and Information related to the activity is provided to the entity to facilitate the entity's decision on whether to send the first content to each target, wherein The entity delivers the first content to the first target via the bidirectional communication channel established between the entity and the first target of the one or more targets; and In response to the first content being delivered, the first target is able to provide feedback to the entity via the bidirectional communication channel. 45. The method of claim 44, wherein identifying one or more targets comprises: High-influence targets that identify one or more of the aforementioned targets on social networking platforms; and Identify at least one of the targets that are influenced by the high-influence target on the social networking platform. 46. The method of claim 45, wherein the high-influence target is determined by multiple followers on the social network platform. 47. The method of claim 45, wherein the high-influence target on the social network platform is determined by a classification label associated with the at least one target. 48. The method of claim 45, wherein at least one of the targets affected by the high-influence target includes users who are interested in the high-influence target on the social networking platform. 49. The method of claim 44, further comprising calculating a monetary amount to be charged to the entity based on the influence level of each of the one or more objectives. 50. The method of claim 49, wherein the monetary amount to be charged to the entity is further based on the amount of second content delivered from the entity to each target. 51. A method for online advertising implemented on at least one machine, each machine having at least one processor, storage, and a communication platform connected to a network, the method comprising: Based on information from a first fragment associated with each of the one or more targets and information from a second fragment associated with the entity, one or more targets associated with the entity are identified, wherein the one or more targets are considered to be potentially interested in first content provided by the entity; Provides the option to recommend the entity to one or more targets for attention to the entity; and Based on the response to the recommendation, a connection is established between the entity and each target via a bidirectional communication channel. This connection is either a first type of connection or a second type of connection based on the recommendation relationship between the entity and each target. The entity delivers the first content to the first target via the bidirectional communication channel established between the entity and the first target of the one or more targets; and In response to the first content being delivered, the first target is able to provide feedback to the entity via the bidirectional communication channel. 52. A method for online advertising implemented on at least one machine, each machine having at least one processor, storage, and a communication platform connected to a network, the method comprising: Based on information from a first fragment associated with each of the one or more targets and information from a second fragment associated with the entity, one or more targets associated with the entity are identified, wherein the one or more targets are considered to be potentially interested in first content provided by the entity; Encourage the entity to send invitations to the one or more targets in order to gain their attention; and Based on the response to the invitation, a connection is established between the entity and each target via a two-way communication channel. This connection is either a first-type connection or a second-type connection based on the recommendation relationship between the entity and each target. The entity delivers the first content to the first target via the bidirectional communication channel established between the entity and the first target; and In response to the first content being delivered, the first target is able to provide feedback to the entity via the bidirectional communication channel.