CN112069409B - Method and device based on to-be-done recommendation information, computer system and storage medium - Google Patents
Method and device based on to-be-done recommendation information, computer system and storage medium Download PDFInfo
- Publication number
- CN112069409B CN112069409B CN202010933788.7A CN202010933788A CN112069409B CN 112069409 B CN112069409 B CN 112069409B CN 202010933788 A CN202010933788 A CN 202010933788A CN 112069409 B CN112069409 B CN 112069409B
- Authority
- CN
- China
- Prior art keywords
- information
- backlog
- application
- association
- retrieval
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/109—Time management, e.g. calendars, reminders, meetings or time accounting
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Marketing (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Economics (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the disclosure discloses a method and a device for recommending associated information based on backlog, a computer system and a computer-readable storage medium, and relates to the field of intelligent office. The backlog includes backlog information. The method comprises the following steps: acquiring backlog information; retrieving associated information related to the backlog information; and transmitting the association information. According to the method, intelligent recommendation according to backlog can be achieved, completion of backlog is assisted, and therefore efficiency of solving backlog is improved.
Description
Technical Field
The present disclosure relates to the field of intelligent office, and more particularly, to a method and apparatus, a computer system, and a computer-readable storage medium based on backlog recommendation association information.
Background
The existing functions of the to-do application mainly comprise time management, and the functions of recording backlog, tracking completion progress, reminding and the like are used for assisting a user in time management, so that an effective workflow is established.
Disclosure of Invention
According to a first aspect of the present disclosure, an embodiment of the present disclosure discloses a method of recommending associated information based on backlog, the backlog including backlog information, the method comprising: acquiring the backlog information; retrieving associated information related to the backlog information; and transmitting the association information.
According to a second aspect of the present disclosure, an embodiment of the present disclosure discloses an apparatus for recommending associated information based on backlog, the backlog including backlog information, the apparatus comprising: the first acquisition module is configured to acquire the backlog information; a retrieval module configured to retrieve associated information related to the backlog information; and a transmission module configured to transmit the association information.
According to a third aspect of the present disclosure, embodiments of the present disclosure disclose a computer system comprising: a processor; and a memory storing a computer program that, when executed by the processor, causes the processor to perform the method of recommending association information based on backlog described above.
According to a fourth aspect of the present disclosure, embodiments of the present disclosure disclose a computer-readable storage medium storing a computer program which, when executed by a processor of a computer system, causes the computer system to perform the above-described method of recommending associated information based on backlog.
According to a fifth aspect of the present disclosure, embodiments of the present disclosure disclose a computer program product comprising a computer program which, when executed by a processor, implements the method of backlog recommendation related information described above.
According to one or more embodiments of the present disclosure, by acquiring backlog information, retrieving associated information related to the backlog information, and transmitting the associated information, intelligent recommendation according to backlog may be implemented, and completion of backlog may be assisted, thereby improving efficiency in solving backlog problems.
Drawings
The accompanying drawings illustrate exemplary embodiments and, together with the description, serve to explain exemplary implementations of the embodiments. The illustrated embodiments are for exemplary purposes only and do not limit the scope of the claims. Throughout the drawings, identical reference numerals designate similar, but not necessarily identical, elements.
FIG. 1 illustrates an exemplary system architecture diagram in which embodiments of the present disclosure may be used;
FIG. 2 illustrates a flow chart of a method of recommending associated information based on backlog in accordance with an embodiment of the present disclosure;
FIG. 3 illustrates a flow chart of a method of generating a set of historical information according to an embodiment of the present disclosure;
FIG. 4 illustrates a flow chart of a method of relating information based on a to-do recommendation in accordance with another embodiment of the present disclosure;
FIG. 5 illustrates a flow chart of a method of ranking retrieved associated information according to an embodiment of the present disclosure;
FIG. 6 illustrates a block diagram of an apparatus based on backlog recommendation association information, according to an embodiment of the present disclosure; and
FIG. 7 illustrates a block diagram of an exemplary computer system that can be used to implement embodiments of the present disclosure.
Detailed Description
The present disclosure is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. In addition, for convenience of description, only a portion related to the related invention is shown in the drawings.
It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other. Unless the context clearly indicates otherwise, the elements may be one or more if the number of the elements is not specifically limited. In addition, the numbers of the steps or the functional modules used in the present disclosure are only used to identify the respective steps or the functional modules, and are not used to limit the execution order of the respective steps or the connection relationship of the respective functional modules to each other.
The current to-do application mainly has the functions of to-do management and task management of individuals or teams, and the ordered development of the individual or team work is assisted through effective time management. However, the existing to-do application lacks a recommending function of information associated with to-do items, and cannot quickly obtain summary information of experiences of related products, services, technologies, and the like.
In view of the above problems of the current backlog application, the present disclosure provides a method for recommending related information based on backlogs, so as to implement intelligent recommendation according to backlogs and assist completion of backlogs, thereby improving efficiency of solving backlogs. Methods and apparatuses for associating information based on backlog recommendations according to embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
FIG. 1 illustrates an exemplary system architecture 100 of an embodiment of a method or apparatus based on to-do recommendation-related information of the present disclosure may be used.
As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc., wherein the wireless connection may include, but is not limited to, 3G/4G connections, wiFi connections, bluetooth connections, wiMAX connections, zigbee connections, UWB (ultra wideband) connections, and other now known or later developed wireless connection means.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like.
The terminal devices 101, 102, 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices having a display screen and supporting information input, including but not limited to: various mobile computing devices, such as smartphones, tablet computers, laptop computers, personal Digital Assistants (PDAs), electronic book readers, MP3 (Moving Picture Experts Group Audio Layer III, dynamic imaging expert compression standard audio plane 3) players, MP4 (Moving Picture Experts Group Audio Layer IV, dynamic imaging expert compression standard audio plane 4) players, wearable computing devices (e.g., smartwatches, smartglasses, smartbracelets, headsets, etc.), or other types of mobile devices; and various stationary computing devices such as desktop computers and the like. Various communication client applications, such as a backlog application, an office system application, a web browser application, a shopping application, a search application, an instant messaging tool, a mailbox client, social platform software, and the like, may be installed on the terminal devices 101, 102, 103.
When the terminal devices 101, 102, 103 are software, they can be installed in the above-listed electronic devices. It may be implemented as multiple software or software modules (e.g., to provide distributed services), or as a single software or software module, such as various communication client applications described above, such as backlog class applications, office system applications, web browser applications, shopping class applications, search class applications, instant messaging tools, mailbox clients, social platform software, and the like. The present invention is not particularly limited herein.
The server 105 may be a server that provides various services, such as a background server that provides support for backlog information transmitted by the terminal devices 101, 102, 103. The background server may analyze and process the received data such as backlog information, and may feed back a processing result (for example, related information related to the backlog) to the terminal devices 101, 102, 103.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster formed by a plurality of servers, or as a single server. When server 105 is software, it may be implemented as a plurality of software or software modules (e.g., to provide distributed services), or as a single software or software module. The present invention is not particularly limited herein.
It should be noted that, the method based on the to-do recommendation related information provided by the embodiments of the present disclosure is generally performed by the server 105. Accordingly, the means for recommending the associated information based on backlog is generally provided in the server 105.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
A method based on the to-do recommendation-related information is described in detail below with reference to fig. 2, wherein fig. 2 shows a flowchart of a method based on the to-do recommendation-related information according to an embodiment of the present disclosure. The method 200 of recommending association information based on backlog may include: step S202, obtaining backlog information; step S204, searching the related information related to the backlog information; and step S206, transmitting the association information. Wherein the backlog includes backlog information. Here, the execution subject (e.g., the server 105 shown in fig. 1) of the method of recommending the related information based on backlog may acquire the backlog information transmitted from the terminal device (e.g., the terminal devices 101, 102, 103 shown in fig. 1) through the network (e.g., the network 104 shown in fig. 1), and after acquiring the backlog information, the execution subject retrieves the related information based on the backlog information and transmits the retrieved related information to the terminal device through the network. By the method, intelligent recommendation according to backlog can be realized, completion of the backlog is assisted, and therefore efficiency of solving the backlog is improved.
In some embodiments, backlogs may include personally created backlogs and/or backlogs assigned by applications, such as office applications. The backlog created by the person can be input through an application page of the terminal device. Backlogs allocated by applications, such as office applications, may be backlogs allocated by online applications from a company's conference system, session system, task system, project system, and OKR (Objectives and Key Results, goal and key achievement) system, etc., and displayed on an application page of the terminal device. In some embodiments, the to-do information may include at least one of the following: time, creator, participant, to-Do topic, to-Do details, document content, and to-Do source.
In some embodiments, the backlog information may be acquired in response to a request from a user, so that targeted retrieval may be performed, and the calculation amount of the retrieval operation may be reduced. Alternatively, the backlog information may be acquired in response to generation of the backlog.
In some embodiments, online retrieval of associated information related to the to-do information from the search engine may be initiated. The search engine is a system for searching out related information from the Internet by using a specific strategy according to search requirements and feeding back the related information. That is, the execution body is connected with at least one search engine, the acquired backlog information is transmitted to the search engine, and the search engine retrieves the associated information from the internet in response to the received backlog information and returns the associated information to the execution body. For example, for a backlog of the backlog topic "grab WeChat public number resource", the execution subject sends the backlog information to the search engine, and then the search engine performs online search for related information related to the backlog of "grab WeChat public number resource", such as what is the grab, how to grab, and the tool of the application, etc., according to the backlog information, and returns to the execution subject. Therefore, the knowledge of the whole network can be integrated to conduct intelligent recommendation of backlog, completion of backlog is assisted, and therefore problem solving efficiency is improved.
In some embodiments, the associated information related to the to-do information may also be retrieved from at least one historical information from at least one application, such as an office application. The office application refers to a system used for office in any company, and comprises a to-be-handled system, a document system, a project system, a task system, a OKR system, a conference system, a week report system and the like. The history information comprises experience summaries of products, services, technologies and the like, platform tools, proper noun interpretation, participation personnel and the like. That is, the execution subject is connected to at least one application in the company, and at least one history information acquired from the at least one application is used for retrieval of the related information related to the backlog. For example, for a backlog of the backlog topic "grab WeChat public number resource," the execution subject may retrieve, from history information acquired from the office application according to the backlog information, associated information related to the backlog of "grab WeChat public number resource," such as what is a grab, similar task or backlog performed by the participants of the backlog, other team or personal information that has performed similar task or is performing similar backlog, related experience of other team or person performing similar task, and platform and tools of the application, etc. Therefore, the intelligent recommendation of the backlog can be performed by integrating the knowledge and experience of the person, team or company, and the completion of the backlog is assisted, so that the efficiency of solving the backlog is improved. Alternatively, in some embodiments, the history information may include a full amount of history information from all applications of the company, including office applications.
As described above, in some embodiments, before retrieving the associated information related to the to-do information from the history information from at least one application, such as an office application, the executing entity needs to generate a set of history information for retrieval. In some embodiments, as shown in fig. 3, the method may further comprise: step S302, at least one history information from at least one application, such as an office application, is acquired; and step S304 of storing at least one history information from at least one application, such as an office application. Wherein the retrieving and storing of at least one history information from at least one application may be performed concurrently with the retrieving of the associated information, in addition to the retrieving of the associated information, but it is to be understood that the present disclosure is not limited thereto. Therefore, the intelligent recommendation of the backlog can be performed by integrating the knowledge and experience of the person, team or company, and the completion of the backlog is assisted, so that the efficiency of solving the backlog is improved.
In some embodiments, the history information may include history information collected through a collection SDK (software development kit ) implanted in each application, thereby making the collected history information more secure and stable. The SDK collection is a software package which is developed based on each office system and has the functions of collection and the like, and comprises a front end and a server. The front end (equivalent to a data interface) is implanted in each application and used for collecting the historical information data, the collected historical information data is transmitted to the server through a wired connection mode or a wireless connection mode, and then the server sends the collected historical information data to the execution main body. The wireless connection may include, but is not limited to, 3G/4G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection.
In some embodiments, retrieval of associated information is inconvenient because at least one of the historical information obtained from at least one application, such as an office application, is unstructured data (including documents, reports, pictures, audio, etc.). Thus, the acquired at least one history information from the at least one application may be stored structurally, i.e. the data is stored in a fixed format (e.g. in tabular form).
In some embodiments, as further shown in fig. 3, to improve the retrieval quality and efficiency, the method may further include: step S306, at least one history information from at least one application, such as an office application, is analyzed and an index is generated for retrieval. Wherein, for analyzing at least one history information from at least one application and generating an index for retrieval may occur, for example, after storing the at least one history information from at least one office system, it is to be understood that the disclosure is not so limited.
After the execution body acquires the backlog information, the backlog information can be processed to determine keywords of the backlog information, and the keywords are searched. In some embodiments, as shown in fig. 4, retrieving the associated information related to the to-do information may include: step S402, word segmentation is carried out on the backlog information, and keywords used for searching are generated; and step S404, according to the keywords, the related information related to the backlog information is searched. In this way, the quality and efficiency of the retrieval of the related information related to the backlog can be improved.
Alternatively, in some embodiments, the execution subject may directly retrieve the obtained to-do information as a retrieval word. For example, for a backlog of a backlog topic "grab WeChat public number resource", the relevant information about the backlog topic (i.e., grab WeChat public number resource) is retrieved using the backlog topic as a search term.
In some embodiments, to optimize the backlog-based recommendation, the method may further include: step S406, the retrieved association information is ordered according to preset rules. In some embodiments, the illustrated method may further comprise: step S408, at least one association information is selected from the sorted association information for transmission. That is, by selecting a certain amount of associated information from the sorted associated information, the associated information with low reference value is filtered out, so that the recommendation result based on backlog is optimized, and the completion efficiency of backlog is improved.
In some embodiments, as shown in fig. 5, sorting the retrieved association information according to the preset rule may include: step S502, calculating the relevance of each piece of the searched relevant information and the key words used for searching by using a relevance calculation model; step S504, sorting the retrieved association information based on the calculated correlation. It should be understood that the higher the correlation between the related information and the backlog information, the more valuable the reference is, so the retrieved related information can be ranked according to the correlation, so as to optimize the recommendation result based on the backlog and improve the completion efficiency of the backlog. Where the relevance calculation model refers to a machine learning model, including but not limited to LR (Logistic Regression ), GBDT (Gradient Boosting Decision Tree, gradient boosting decision tree), DNN (Deep Neural Networks, deep neural network), etc., it should be understood that the present disclosure may also use other relevance algorithms (such as word frequency statistics algorithm, mutual information algorithm, expected cross entropy) to calculate the relevance of each of the retrieved relevance information to the keywords used for retrieval.
In some embodiments, after the executing body transmits the association information, the method further comprises: step S506, adaptively training the correlation calculation model in response to the user operation on the transmitted correlation information. For example, when a user selects to be irrelevant for a certain transmitted association information on a terminal device, in response to this operation by the user, the execution subject transmits the irrelevant association information to the correlation calculation model for adaptive training. Therefore, the recommendation result based on the backlog can be optimized in a self-adaptive mode, and the completion efficiency of the backlog is improved.
After retrieving the related information related to the backlog, the execution subject transmits the retrieved related information to the terminal device through the network. In some embodiments, the executing entity may send the retrieved associated information in the form of a list, where the list of associated information may include, for example, a list of related knowledge, a list of related tools, a list of related teams or individuals, and so forth. For example, for a backlog entitled "capture WeChat public number resource" for a backlog, the executive body will send a relevant knowledge information list (in turn, methods of data capture, flows of data capture, data capture cleanup, etc.), a relevant tools list (in turn, tools A, platform B, tools C), a relevant team, and a relevant person (in turn, team D, team E, person F, etc.).
In summary, according to the method for recommending the associated information based on the backlog according to the embodiment of the disclosure, intelligent recommendation according to the backlog can be achieved, completion of the backlog is assisted, and therefore efficiency of solving the backlog is improved.
Fig. 6 is a block diagram illustrating a structure of an apparatus 600 based on backlog recommendation-related information according to an embodiment of the present disclosure. As shown in fig. 6, the backlog recommendation association information-based apparatus 600 may include a first acquisition module 601 configured to acquire backlog information, a retrieval module 602 configured to retrieve association information related to the backlog information, and a transmission module 603 configured to transmit the association information.
In some embodiments, as shown in fig. 6, the apparatus 600 for recommending association information based on backlog may further include: a second acquisition module 604 configured to acquire at least one history information from at least one application and a storage and indexing module 605 configured to store at least one history information from at least one application and analyze at least one history information from at least one application and generate an index for retrieval.
In this embodiment, the specific implementation manner and technical effects of the device 600 based on the to-do recommendation related information and the corresponding functional modules thereof may refer to the related descriptions in the embodiments described in fig. 2 and 3, and are not described herein again.
FIG. 7 is a block diagram illustrating an exemplary computer system that can be used to implement embodiments of the present disclosure. A computer system 700 suitable for use in implementing embodiments of the present disclosure is described below in connection with fig. 7. It should be appreciated that the computer system 700 depicted in fig. 7 is only an example and should not be taken as limiting the functionality and scope of use of the embodiments of the present disclosure.
As shown in fig. 7, a computer system 700 may include a processing device (e.g., a central processing unit, a graphics processor, etc.) 701, which may perform various suitable actions and processes in accordance with a program stored in a Read Only Memory (ROM) 702 or a program loaded from a storage device 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the computer system 700 are also stored. The processing device 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
In general, the following devices may be connected to the I/O interface 705: input devices 706 including, for example, a touch screen, touch pad, camera, accelerometer, gyroscope, etc.; an output device 707 including, for example, a liquid crystal display (LCD, liquid Crystal Display), a speaker, a vibrator, and the like; storage 708 including, for example, flash memory (Flash Card) or the like; and a communication device 709. The communication means 709 may allow the computer system 700 to communicate wirelessly or by wire with other devices to exchange data. While FIG. 7 illustrates a computer system 700 having various devices, it should be understood that not all illustrated devices are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 7 may represent one device or a plurality of devices as needed.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure provide a computer readable storage medium storing a computer program comprising program code for performing the method 200 shown in fig. 2. In such an embodiment, the computer program may be downloaded and installed from a network via communication device 709, or installed from storage 708, or installed from ROM 702. The above-described functions defined in the apparatus of the embodiments of the present disclosure are achieved when the computer program is executed by the processing apparatus 701.
It should be noted that, the computer readable medium according to the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In an embodiment of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. Whereas in embodiments of the present disclosure, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (Radio Frequency), and the like, or any suitable combination thereof.
The computer readable medium may be embodied in the computer system 700; or may exist alone without being assembled into the computer system 700. The computer readable medium carries one or more programs which, when executed by the computing device, cause the computer system to: the backlog information is acquired, the association information related to the backlog information is retrieved, and the association information is transmitted.
Computer program code for carrying out operations of embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules referred to in the embodiments described in the present disclosure may be implemented in software or hardware. The described modules may also be provided in a processor, for example, as: a processor comprises a first acquisition module, a retrieval module and a sending module. The names of these modules do not constitute a limitation on the module itself in some cases.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.
Claims (12)
1. A method of recommending associated information based on backlog, the backlog comprising backlog information, the method comprising:
acquiring backlog information;
analyzing at least one history information from at least one application, the at least one history information including information collected by a collection SDK implanted in the at least one application, and generating an index for retrieval;
retrieving associated information related to the backlog information from at least one history information from the at least one application;
ordering the retrieved association information according to a preset rule, including:
calculating the relevance of each piece of the searched relevant information and the keyword for searching by using a relevance calculation model; and
ranking the retrieved association information based on the calculated correlation;
transmitting the association information; and
the correlation calculation model is adaptively trained in response to user operations on the transmitted correlation information.
2. The method of claim 1, wherein the method further comprises:
acquiring the at least one history information from the at least one application; and
storing the at least one history information from the at least one application.
3. The method of claim 1, wherein the method further comprises:
an online retrieval of the association information from the search engine is initiated.
4. The method of any of claims 1-3, wherein the retrieving association information related to the to-do information comprises:
cutting words from the backlog information to generate keywords for retrieval; and
and according to the keywords, retrieving the associated information related to the backlog information.
5. The method of claim 1, wherein the method further comprises:
at least one association information is selected from the ordered association information for transmission.
6. The method of claim 1, wherein the to-do information is obtained in response to a user request based on the to-do recommendation-related information.
7. The method of claim 1, wherein the backlog comprises at least one of: personally created backlog and assigned backlog.
8. The method of claim 1, wherein the backlog information comprises at least one of: creator, participant, to-do topic, to-do details, document content, and to-do source.
9. An apparatus that recommends associated information based on backlog, the backlog including backlog information, the apparatus comprising:
a first acquisition module configured to: acquiring the backlog information;
a storage and indexing module configured to: analyzing at least one history information from at least one application, the history information including information collected by a collection SDK implanted in the at least one application, and generating an index for retrieval;
a retrieval module configured to:
retrieving associated information related to the backlog information from at least one history information from the at least one application; and
ordering the retrieved association information according to a preset rule, including:
calculating the relevance of each piece of the searched relevant information and the keyword for searching by using a relevance calculation model; and
ranking the retrieved association information based on the calculated correlation; and
a transmission module configured to:
transmitting the association information; and
the correlation calculation model is adaptively trained in response to user operations on the transmitted correlation information.
10. The apparatus of claim 9, wherein the apparatus further comprises:
a second acquisition module configured to acquire at least one history information from at least one application, and
wherein the storage and indexing module is further configured to: storing the at least one history information from the at least one application.
11. A computer system, comprising:
a processor; and
memory storing a computer program which, when executed by the processor, causes the processor to perform the method according to any one of claims 1-8.
12. A computer readable storage medium storing a computer program which, when executed by a processor of a computer system, causes the computer system to perform the method of any one of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010933788.7A CN112069409B (en) | 2020-09-08 | 2020-09-08 | Method and device based on to-be-done recommendation information, computer system and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010933788.7A CN112069409B (en) | 2020-09-08 | 2020-09-08 | Method and device based on to-be-done recommendation information, computer system and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112069409A CN112069409A (en) | 2020-12-11 |
| CN112069409B true CN112069409B (en) | 2023-08-01 |
Family
ID=73664252
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010933788.7A Active CN112069409B (en) | 2020-09-08 | 2020-09-08 | Method and device based on to-be-done recommendation information, computer system and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112069409B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115907358B (en) * | 2022-11-10 | 2023-10-20 | 百度时代网络技术（北京）有限公司 | Method, device and system for processing tasks to be handled and electronic equipment |
| CN116629810B (en) * | 2023-07-24 | 2023-10-20 | 中建五局第三建设有限公司 | Operation recommendation method, device, equipment and medium based on building office system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104011504A (en) * | 2011-12-27 | 2014-08-27 | 英特尔公司 | Method, system, and device for to-do-list based navigation |
| CN106327158A (en) * | 2016-08-24 | 2017-01-11 | 深圳Tcl新技术有限公司 | Backlog item prompting method and intelligent terminal |
| CN109409532A (en) * | 2017-08-14 | 2019-03-01 | 埃森哲环球解决方案有限公司 | Product development based on artificial intelligence and machine learning |
| CN110581794A (en) * | 2018-06-11 | 2019-12-17 | 腾讯科技（深圳）有限公司 | Information processing method, information processing device, storage medium and computer equipment |
| CN110889263A (en) * | 2019-10-24 | 2020-03-17 | 北京字节跳动网络技术有限公司 | Document backlog generation method, device, equipment and storage medium |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9460095B2 (en) * | 2011-11-28 | 2016-10-04 | Microsoft Technology Licensing, Llc | Quick capture of to-do items |
| US9384467B2 (en) * | 2012-12-18 | 2016-07-05 | Google Inc. | Providing actionable notifications to a user |
| US20140278718A1 (en) * | 2013-03-15 | 2014-09-18 | International Business Machines Corporation | Enhanced time-management and recommendation system |
-
2020
- 2020-09-08 CN CN202010933788.7A patent/CN112069409B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104011504A (en) * | 2011-12-27 | 2014-08-27 | 英特尔公司 | Method, system, and device for to-do-list based navigation |
| CN106327158A (en) * | 2016-08-24 | 2017-01-11 | 深圳Tcl新技术有限公司 | Backlog item prompting method and intelligent terminal |
| CN109409532A (en) * | 2017-08-14 | 2019-03-01 | 埃森哲环球解决方案有限公司 | Product development based on artificial intelligence and machine learning |
| CN110581794A (en) * | 2018-06-11 | 2019-12-17 | 腾讯科技（深圳）有限公司 | Information processing method, information processing device, storage medium and computer equipment |
| CN110889263A (en) * | 2019-10-24 | 2020-03-17 | 北京字节跳动网络技术有限公司 | Document backlog generation method, device, equipment and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| 基于即时消息软件待办信息推送系统的设计与实现;曾小斌;;信息安全与技术(02);全文 * |
| 综合社区与关联序列挖掘的电子政务推荐算法;黄亚坤;王杨;王明星;;计算机应用(09);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112069409A (en) | 2020-12-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107679211B (en) | Method and device for pushing information | |
| CN108804450B (en) | Information pushing method and device | |
| CN111125574B (en) | Method and device for generating information | |
| WO2017071251A1 (en) | Information pushing method and device | |
| US9773065B2 (en) | Providing relevant information to a user based upon monitored user activities in one or more contexts | |
| CN104199863B (en) | Lookup method, device and the router of file in storage device | |
| US9949149B2 (en) | Online and distributed optimization framework for wireless analytics | |
| CN110059172B (en) | Method and device for recommending answers based on natural language understanding | |
| US10733249B1 (en) | Machine learning system for data selection | |
| CN110866040B (en) | User portrait generation method, device and system | |
| US20180121849A1 (en) | Personalized Aggregated Activity Feed | |
| CN112241327A (en) | Shared information processing method and device, storage medium and electronic equipment | |
| WO2025016255A1 (en) | Task processing method and automatic question answering method | |
| CN110020126B (en) | Content selection and presentation of electronic content | |
| CN112069409B (en) | Method and device based on to-be-done recommendation information, computer system and storage medium | |
| CN113076417A (en) | Policy file data processing method and device | |
| US9367624B2 (en) | Identity workflow that utilizes multiple storage engines to support various lifecycles | |
| CN113807926A (en) | Recommendation information generating method, apparatus, electronic device and computer readable medium | |
| CN111770125A (en) | Method and apparatus for pushing information | |
| US11799734B1 (en) | Determining future user actions using time-based featurization of clickstream data | |
| CN108509442B (en) | Search method and apparatus, server, and computer-readable storage medium | |
| CN113269600B (en) | Information sending method and device | |
| CN111382365B (en) | Method and device for outputting information | |
| CN112950239B (en) | Method, apparatus, device and computer readable medium for generating user information | |
| US20220253962A1 (en) | Computer-implemented system and methods for generating crime solving information by connecting private user information and law enforcement information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |