CN101350154B - Method and device for sorting electronic map data - Google Patents

Abstract

The invention discloses a priority method of electronic map data and a device, which solves the problem that a traditional artificial priority method causes a poor priority effect, wastes manpower and has high cost. The method comprises that a key word of each electronic map data is extracted, web sets of search results, which correspond to each electronic map data are obtained through that the key word is used to search. According the corresponding wet sets of search results of each electronic map data, the importance of the electronic map data is calculated, and the electronic map data is sorted according to the importance. The invention uses the internet popularity of internet to depict the importance degree of POI data, because the depiction represents the recognition of vast netizen even broad masses, the priority effect is better and has excellent mass basis and rationality. Further, a machine is used to automatically score and sort, thereby the man labor is effectively saved, the efficiency is higher, and the cost is very low.

Description

Method and device for sorting electronic map data

technical field

The invention relates to the field of network technology, in particular to a sorting method and device for electronic map data.

Background technique

With the development and improvement of geographic information system, the design and development technology of electronic map is becoming more and more mature. In electronic maps, there is a type of data called point of interest data (Point of Interest, POI data), which refers to data that people are interested in, such as geographic information of restaurants, parks, shopping malls and other buildings, or information about some streets, etc. wait. Usually, POI data includes information on four aspects: name, category, longitude, and latitude, and sometimes other information, such as address, phone number, zip code, and so on. POI data is one of the most important elements of electronic maps, and it is also the information that people pay most attention to when using electronic maps.

An electronic map usually contains a lot of POI data, and these POI data cover most of the geographical information within the range of the map. However, the importance of geographic information in the electronic map is different. For example, "Tiananmen Square" is more important than "Zhongguancun Square", and "Peking University" is more important than "Peking University High School". This difference in the importance of geographic information leads to POI The importance of data varies.

POI sorting refers to the sorting of POI data according to the importance of POI data. The importance of POI data is reflected in the importance of the geographic information it refers to. POI sorting can be applied in the sorting of search engines, that is, sorting and displaying the query results of electronic maps according to the importance of POI data.

At present, there is no relatively mature POI sorting method. Traditionally, developers of electronic maps will invite some editors or ordinary people to sort POI data according to people's familiarity with POI data. The core idea of sorting according to familiarity is: if a POI data refers to Geographic location is very important, then it must be familiar to people. This idea is reasonable to a certain extent. Since the users of electronic maps and even actual geographic information are ordinary people, geographic information familiar to ordinary people should be of high importance.

However, this method has the following problems:

First, although familiarity can be used to describe the importance of POI data, how to calculate familiarity is a very difficult problem. Therefore, the above-mentioned manual sorting method cannot represent the vast number of users because only a small number of people participate, so the sorting effect is not guaranteed, and the sorting effect is poor; and, because the number of people is small, the error rate is also relatively high.

Second, due to the large amount of POI data and the rapid update, manual sorting is very labor-intensive and expensive.

Therefore, this manual sorting method cannot be practically used.

Contents of the invention

The invention provides a sorting method and device for electronic map data to solve the problems of poor sorting effect, manpower consumption and high cost caused by the traditional manual sorting method.

In order to solve the above technical problems, according to the specific embodiments provided by the invention, the invention discloses the following technical solutions:

A method for sorting electronic map data, comprising:

Extract keywords of each electronic map data;

Using the keyword search to obtain a set of search result webpages corresponding to each electronic map data;

For each search result webpage in the collection, calculate the first numerical value used to represent the importance of the webpage and the second numerical value used to represent the degree of matching between the webpage and the keyword, according to the first numerical value and the second numerical value of all search result webpages in the corresponding collection Two values, calculating the importance of the electronic map data;

sorting the electronic map data according to the importance;

Wherein, the calculating the importance of the electronic map data according to the first value and the second value of all the search result web pages in the corresponding set specifically includes: comparing the first value and the second value of each search result web page in the set and then sum the multiplication results of all the search result webpages in the collection to obtain the importance of the electronic map data.

Preferably, the first value is obtained by calculating the web page rank.

Preferably, after the calculation of the importance of the electronic map data, it further includes: according to the different weights of the categories to which the electronic map data belongs, multiplying the importance of the electronic map data by the weight value of the category to which the electronic map data belongs, Get the adjusted result data for sorting.

Wherein, the extracting the keyword of each electronic map data specifically includes: extracting the name of each electronic map data as the keyword.

Preferably, the method also includes: extracting the address information of each electronic map data, and using the name together as a keyword.

Preferably, before extracting the keywords of each electronic map data, it also includes: preprocessing the original electronic map data, the preprocessing includes removing irrelevant symbols, character code conversion, and adjusting the unified format; The results are used for keyword extraction;

Preferably, after sorting the electronic map data according to the importance, it also includes: in the electronic map retrieval, returning matching search results according to the query words input by the user, and sorting the top ranked electronic maps in the search results Data is displayed first.

Preferably, after sorting the electronic map data according to the importance, the method further includes: when displaying the layers, selecting and displaying the top-ranked electronic map data within the display range.

Preferably, after sorting the electronic map data according to the importance, the method further includes: prioritizing updating of the electronic map data ranked higher.

The present invention also provides a sorting device for electronic map data, comprising:

A keyword extraction unit is used to extract keywords of each electronic map data;

a query unit, configured to use the keyword to search, and obtain a set of search result webpages corresponding to each electronic map data;

The calculation unit includes: a first calculation subunit, for each search result webpage in the collection, respectively calculating a first numerical value representing the importance of the webpage; a second calculation subunit, for each search result webpage in the collection The webpage is used to calculate the second numerical value used to represent the degree of matching between the webpage and the keyword; the comprehensive calculation subunit is used to calculate the second numerical value according to the first numerical value and the second numerical value of all search result webpages in the corresponding set of each electronic map data. The importance of electronic map data;

a sorting unit, configured to sort the electronic map data according to the importance;

Wherein, the comprehensive calculation subunit multiplies the first value and the second value of each search result webpage in the collection, and then sums the multiplication results of all the search result webpages in the collection to obtain the important value of the electronic map data. Spend.

Preferably, the first calculation subunit obtains the first value by calculating the webpage level.

Preferably, the device further includes: an adjustment unit, configured to multiply the importance of the electronic map data by the weight value of the category to which the electronic map data belongs according to the different weights of the category to which the electronic map data belongs, to obtain the adjusted The resulting data, and output to the sort unit for sorting.

Wherein, the keyword extracting unit uses the name of the extracted electronic map data as a keyword.

Preferably, the keyword extracting unit also uses the extracted address information of the electronic map data together with the name as keywords.

Preferably, the device further includes: a preprocessing unit, configured to preprocess the original electronic map data, and output the preprocessing result to the keyword extraction unit; wherein, the preprocessing includes removing irrelevant symbols, character encoding Convert and adjust the unified format.

Preferably, the device further includes: a retrieval unit, configured to return matching retrieval results according to the query words input by the user during the electronic map retrieval, and preferentially display the electronic map data ranked first in the retrieval results.

Preferably, the device further includes: a layer display unit, configured to select and display the top-ranked electronic map data within the display range when the layer is displayed.

Preferably, the device further includes: a data update unit, configured to update the electronic map data ranked first.

The present invention also provides a search engine system, which includes the device described in any one of the above device embodiments.

According to the specific embodiments provided by the invention, the invention has the following technical effects:

First of all, the present invention uses Internet technology to sort POI data, and uses Internet network popularity to describe the importance of POI data, and network popularity is the result webpage returned in the search engine according to keywords (extracted from POI data) Get calculated. Since this kind of description represents the understanding of the majority of netizens and even the general public, the use of Internet popularity to sort POI data has a better sorting effect and has a good mass base and rationality. Moreover, the use of machines to automatically score and sort POI data greatly saves manpower, is more efficient, and costs are very low.

Secondly, when using network popularity to describe the importance of POI data, the present invention mainly uses two indicators, the importance of web pages and the matching degree of web pages and keywords, and each index also has a different calculation method.

Again, the present invention also fully considers the impact of the category of POI data on the importance of POI, and uses the category information of POI data to adjust the basic network popularity score to obtain the final score of POI, thereby more accurately describing the POI data. Importance.

Description of drawings

Fig. 1 is a flowchart of a method for sorting electronic map data according to Embodiment 1 of the present invention;

2 is a schematic flow chart of a method for sorting POI data according to Embodiment 2 of the present invention;

Fig. 3 is a structural diagram of an electronic map data sorting device according to an embodiment of the present invention.

Detailed ways

In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

Embodiment one:

Aiming at the traditional POI manual sorting method, the embodiment of the present invention provides a sorting method using Internet technology. Referring to FIG. 1 , it is a flowchart of a method for sorting electronic map data according to Embodiment 1 of the present invention. In this embodiment, the electronic map data is described by taking POI data as an example, but the electronic map data includes but not limited to POI data.

S101, extracting keywords of each POI data;

In this embodiment, a keyword needs to be extracted from each POI data to be used for querying in an Internet search engine. Since each POI data has some attributes, including name, category, coordinates or other attribute information, the words that best represent the POI data can be extracted from these attribute information as keywords during extraction. In this embodiment, the basic part of the keyword is the name of the POI, because the name is the most important part of the POI data.

Preferably, when extracting the name of the POI data, some processing needs to be performed on the name, such as removing information such as branches and branches in the name. Because there are often branches and branches in names such as catering and companies, and the purpose of POI sorting is to rank the head office and head office at the top, so this kind of branch and branch can be ranked at this time. Company characters removed. For example, "xx company Wudaokou branch", you can remove "Wudaokou branch", leaving only "xx company".

Preferably, some other information can also be added as a supplement to the name, such as address, district and county, etc. Because some names are too short to have practical meaning, such as public toilet, parking lot, etc., at this time, you can add the address of the POI and use it as a keyword together with the name, so that the processing effect is better.

S102, using the keyword to search, and obtaining a set of search result webpages corresponding to each POI data;

The keywords extracted above are queried in a search engine and a returned result set is obtained.

S103. Calculate the importance of the POI data according to the corresponding search result web page set of each POI data;

The present invention uses the network popularity of the Internet to describe the importance of POI data, and the network popularity of POI is calculated according to the set of search result webpages corresponding to the POI. Wherein, the network popularity refers to the degree of popularity of a name in the network.

For each POI data, multiple search result pages (that is, a collection of web pages) can be obtained by using the extracted keywords to query, and each web page has two indicators: one is the importance of the web page, and the other is the web page and keyword. degree of matching. In this embodiment, the above two indicators are mainly used to measure the network popularity of POI data.

Since each indicator has a different calculation method, this embodiment only adopts one of the commonly used methods. For the importance of the webpage, a method of calculating the webpage rank (PageRank) is adopted. The PageRank of a webpage is an indicator to measure the importance of a webpage. It is calculated based on the hyperlinks between webpages and originated from the PageRank algorithm proposed by the founder of Google. Of course, the web page traffic can also be used to indicate the importance of the web page. For the matching degree (MatchRank) between a web page and a keyword, the calculation method usually adopted is: if the keyword appears completely in the web page, the matching degree is high; if the keyword appears after being segmented, the matching degree is low. The present invention includes but is not limited to the above calculation methods.

After obtaining the PageRank and MatchRank of each webpage, multiply the PageRank and MatchRank of each webpage, and then add the multiplication results of all webpages corresponding to the same POI data to obtain a calculation result of POI data. In this embodiment, the method of scoring POI data is adopted, so the calculation result is a score describing the network popularity of the POI data.

It should be noted that the above method of obtaining a POI score by multiplying and adding the PageRank and MatchRank of the webpage is only an implementation of this embodiment, and the present invention includes but is not limited to the method.

S104, sort the POI data according to the importance.

After obtaining the score of each POI data, all POI data can be sorted by using the score.

As can be seen from the above processing flow, the present invention uses the network popularity of the Internet to describe the importance of POI data. Since this description represents the understanding of the majority of netizens and even the general public, the network popularity is used to sort the POI data. The effect of sorting is compared. Well, it has a good mass base and rationality. Moreover, the use of machines to automatically score and sort POI data greatly saves manpower, is more efficient, and costs are very low.

Embodiment two:

Embodiment 2 of the present invention provides a specific application example.

Referring to FIG. 2 , it is a schematic flowchart of a method for sorting POI data according to Embodiment 2 of the present invention.

S201, preprocessing the original POI data;

The main function of cleaning and filtering the original POI data is to make the data meet certain input standards. The preprocessing mainly includes three parts: removal of irrelevant symbols, conversion of character codes, and adjustment of unified format. in,

1) Remove irrelevant symbols: Due to the source of the data or other problems, there may be some irrelevant symbols in the data, these symbols have no practical meaning, such as! , # and other symbols, as well as garbled characters, etc., these irrelevant symbols need to be removed to play a cleaning and filtering role;

2) Character encoding conversion: Make the encoding of characters consistent, which can be beneficial to the fairness of scoring later. Such as half-width to full-width, traditional to simplified, etc.;

3) Adjust the format: the input format of the data should be unified, which is convenient for programming.

S202, extracting keywords of each POI data for the preprocessed POI data;

During the extraction process, information such as branches and branches contained in the name can be identified according to the geographical name database and alias database, and then these information can be removed. For example " Wudaokou branch of xx company ", if " Wudaokou " is a word in the place-name database, " branch " is the word in the special lexicon, so just can remove " Wudaokou branch ", only remaining " xx company ".

S203, use the keyword to search, and obtain a set of search result webpages corresponding to each POI data;

S204, for each POI data, calculate and obtain a basic score for indicating the importance of the POI data according to the corresponding search result webpage set;

In this embodiment, the score calculated according to the PageRank and MatchRank of the webpage is used as the basic score of the POI data, and this basic score is a description of the network popularity of the POI data.

S205. Adjust the basic score according to the category information of the POI data;

Since POI data has many categories, and different categories of data have different properties on the network. For example, POI data of catering is more concerned than POI data of government agencies on the Internet, but POI data of government agencies is more important than POI data of catering, because people pay more attention to government agencies in real life Class POI data. Therefore, in order to balance the scores of different categories of POI data, this embodiment introduces category weights, and the basic scores of POIs need to be adjusted according to the category weights, so that the scores of POIs with important categories are increased, and the scores of POIs with unimportant categories are decreased. The weight of the category can be set according to experience, or can be obtained by training using some training data. The adjustment process is: the basic score of POI data is multiplied by the weight of the category to which it belongs, so as to obtain the final score.

For example, there are two POI data, one is Peking University Third Hospital, and the other is Guo Lin's home cooking. Since the names of catering categories appear more frequently on the webpage, the basic score of Guo Lin’s home cooking is 5 points, while the score of Peking University Third Hospital is 4 points. But according to people's experience and habits, hospitals are more important than catering, so the hospital category has a higher weight, which is set to 1.5, while the catering category has a lower weight, which is set to 0.8. In this way, the final scores of the two POIs are respectively: Peking University Third Hospital 4×1.5=6, and Guo Lin’s home cooking 5×0.8=4. Therefore, Peking University Third Hospital has a higher score than Guo Lin's home cooking, and the ranking is higher, which is in line with people's general understanding.

S206. Sorting the POI data according to the adjusted final score.

Comparing Embodiment 1 and Embodiment 2, Embodiment 2 adds a preprocessing process and an adjustment process of basic scores. Embodiment 2 also fully considers the impact of POI data categories on the importance of POIs, and uses the category information of POI data to adjust the basic network popularity score to obtain the final POI score, thereby more accurately describing the importance of POI data. degree.

The sorting of electronic map POI data has many practical values, such as:

1) In terms of query and retrieval: when the user inputs a query word when searching the electronic map, many search results will be returned, and these search results all match the query word, but these results often have different degrees of importance. If the POIs are sorted, the important POIs can be displayed in the front while the matching is performed, and the unimportant ones can be placed in the back, which is more convenient for users to use. For example, if you query "Quanjude", there will be many branches of Quanjude and some affiliated companies or training institutions. They all match this query word, but some affiliated companies and training institutions cannot be displayed in the front, because generally these are not important, but Important head offices or branches should be listed first. Another example: querying Peking University, Peking University and its affiliated institutions will appear, Peking University should be ranked first, but its many affiliated institutions should have a sorting order.

2) In terms of layer display: an electronic map generally consists of many layers. When a user views a certain layer, the POI of the layer should be displayed for the user to view. However, there may be many POIs around the user's point of interest in a certain layer. If all these POIs are displayed, the entire page will be very messy and bloated, which is not conducive to users' viewing. Therefore, it is necessary to select a part of POIs for display according to the degree of importance, so that not only users can view the information they need, but also the overall display effect is better.

3) Data update: Since the POI update speed is faster and the update volume is larger, if the energy is limited, only the more important data can be updated first.

With respect to the above method embodiments, the present invention also provides an embodiment of an electronic map data sorting device. Referring to FIG. 3 , it is a structural diagram of an electronic map data sorting device according to an embodiment of the present invention. Described device mainly comprises:

Keyword extraction unit U32, used to extract the keywords of each electronic map data;

The query unit U33 is used to search by using the keywords to obtain a set of search result webpages corresponding to each electronic map data;

A calculation unit U34, configured to calculate the importance of the electronic map data according to the corresponding search result webpage set of each electronic map data;

A sorting unit U36, configured to sort the electronic map data according to the importance.

Wherein, the calculation unit U34 specifically includes:

The first calculation subunit is used to calculate the first numerical value used to represent the importance of the webpage for each search result webpage in the collection; the importance of the webpage can be represented by the webpage level (PageRank), so the first numerical value It refers to the calculated PageRank; of course, it can also be expressed by the traffic of the webpage;

The second calculation subunit is used to calculate the second numerical value used to represent the matching degree of the webpage and the query word for each search result webpage in the collection; the matching degree (MatchRank) of the webpage and the query word can be calculated by multiple methods ;

The comprehensive calculation subunit is used for calculating, for each electronic map data, the result data indicating the importance of the electronic map data according to the first value and the second value of all the search result web pages in the corresponding set. One calculation method is: the comprehensive calculation subunit multiplies the first value and the second value of each search result web page in the collection, and then sums the multiplication results of all search result web pages in the collection to obtain the electronic The importance value of the map data.

Wherein, the keyword extracting unit U32 uses the name of the extracted electronic map data as a keyword; or uses the extracted address information of the electronic map data together with the name as a keyword. Preferably, when the name is extracted, the information including branch stores and branch companies is removed.

Preferably, in another device embodiment of the present invention, the device further includes an adjustment unit U35, configured to multiply the importance of the electronic map data by the electronic map data according to the different weights of the categories to which the electronic map data belongs. The weight value of the category to which the data belongs is obtained from the adjusted result data, and is output to the sorting unit U36 for sorting.

Preferably, in another device embodiment of the present invention, the device further includes a preprocessing unit U31, configured to preprocess the original electronic map data, and output the preprocessing result to the keyword extraction unit U32; wherein , the preprocessing includes removing irrelevant symbols, performing character code conversion, and adjusting a unified format.

Preferably, in another device embodiment of the present invention, the device further includes a retrieval unit U37, configured to return matching retrieval results according to the query words input by the user during electronic map retrieval, and sort the retrieval results by The previous electronic map data is displayed first.

Preferably, in another device embodiment of the present invention, the device further includes a layer display unit U38, configured to select and display the top-ranked electronic map data within the display range when the layer is displayed.

Preferably, in another device embodiment of the present invention, the device further includes a data update unit U39, configured to update the electronic map data ranked first.

The parts not detailed in the device shown in FIG. 3 can refer to the relevant parts of the method shown in FIG. 1 and FIG. 2 , and will not be described in detail here for the sake of space.

In addition, the present invention also provides a search engine system, which includes the device described in any one of the above device embodiments. The search engine system can provide more high-quality search results in the search application of electronic map data.

The method and device for sorting electronic map data provided by the present invention have been introduced in detail above. In this paper, specific examples have been used to illustrate the principle and implementation of the present invention. The description of the above embodiments is only used to help understanding The method of the present invention and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation and application range. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims (19)

1. A method for sorting electronic map data, comprising: Extract keywords of each electronic map data; Searching by using the keywords to obtain a set of search result webpages corresponding to each electronic map data; For each search result webpage in the collection, calculate the first numerical value used to represent the importance of the webpage and the second numerical value used to represent the degree of matching between the webpage and the keyword, according to the first numerical value and the second numerical value of all search result webpages in the corresponding collection Two values, calculating the importance of the electronic map data; sorting the electronic map data according to the importance; Wherein, the calculation of the importance of the electronic map data according to the first value and the second value of all search result webpages in the corresponding collection specifically includes: Multiply the first value and the second value of each search result webpage in the collection, and then sum the multiplication results of all the search result webpages in the collection to obtain the importance of the electronic map data. 2. The method according to claim 1, characterized in that: the first value is obtained by calculating the web page rank. 3. The method according to claim 1, characterized in that, after calculating the importance of the electronic map data, further comprising: According to the different weights of the category of the electronic map data, the importance of the electronic map data is multiplied by the weight value of the category of the electronic map data to obtain adjusted result data for sorting. 4. method according to claim 1, is characterized in that, described extracting the keyword of each electronic map data, specifically comprises: The name of each electronic map data is extracted as a keyword. 5. The method according to claim 4, further comprising: Extract the address information of each electronic map data, and use it as a keyword together with the name. 6. The method according to claim 1, wherein, before the keyword of each electronic map data is extracted, further comprising: Preprocessing the original electronic map data, the preprocessing includes removing irrelevant symbols, character code conversion, and adjusting the unified format; The preprocessing results are used for keyword extraction. 7. The method according to claim 1, characterized in that, after sorting the electronic map data according to the importance, further comprising: In electronic map retrieval, matching retrieval results are returned according to the query words input by the user, and the top-ranked electronic map data in the retrieval results are preferentially displayed. 8. The method according to claim 1, characterized in that, after sorting the electronic map data according to the degree of importance, further comprising: When the layer is displayed, select the top-ranked electronic map data within the display range for display. 9. The method according to claim 1, characterized in that, after sorting the electronic map data according to the degree of importance, further comprising: Prioritize the update of the top-ranked electronic map data. 10. A sorting device for electronic map data, comprising: A keyword extraction unit is used to extract keywords of each electronic map data; a query unit, configured to use the keyword to search, and obtain a set of search result webpages corresponding to each electronic map data; The calculation unit includes: a first calculation subunit, for each search result webpage in the collection, respectively calculating a first numerical value representing the importance of the webpage; a second calculation subunit, for each search result webpage in the collection The webpage is used to calculate the second numerical value used to represent the degree of matching between the webpage and the keyword; the comprehensive calculation subunit is used to calculate the second numerical value according to the first numerical value and the second numerical value of all search result webpages in the corresponding set of each electronic map data. The importance of electronic map data; a sorting unit, configured to sort the electronic map data according to the importance; Wherein, the comprehensive calculation subunit multiplies the first value and the second value of each search result webpage in the collection, and then sums the multiplication results of all the search result webpages in the collection to obtain the important value of the electronic map data. Spend. 11. The device according to claim 10, wherein the first calculation subunit obtains the first value by calculating the webpage level. 12. The device according to claim 10, further comprising: The adjustment unit is used to multiply the importance of the electronic map data by the weight value of the category of the electronic map data according to the different weights of the categories of the electronic map data to obtain the adjusted result data, and output it to the sorting unit for use for sorting. 13. The device according to claim 10, wherein the keyword extracting unit uses the name of the extracted electronic map data as the keyword. 14. The device according to claim 13, wherein the keyword extracting unit also uses the extracted address information of the electronic map data as keywords together with the name. 15. The device according to claim 10, further comprising: A preprocessing unit is used to preprocess the original electronic map data, and output the preprocessing result to the keyword extraction unit; wherein, the preprocessing includes removing irrelevant symbols, converting character codes, and adjusting a unified format. 16. The device according to claim 10, further comprising: The retrieval unit is used for returning matching retrieval results according to the query words input by the user during the electronic map retrieval, and preferentially displaying the top-ranked electronic map data in the retrieval results. 17. The device according to claim 10, further comprising: The layer display unit is used to select and display the top-ranked electronic map data within the display range when the layer is displayed. 18. The device according to claim 10, further comprising: The data updating unit is used for updating the electronic map data ranked first. 19. A search engine system, characterized in that the system comprises the device according to any one of claims 10 to 18.

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