CN102693248A - Network information searching method and system - Google Patents
Network information searching method and system Download PDFInfo
- Publication number
- CN102693248A CN102693248A CN2011100933382A CN201110093338A CN102693248A CN 102693248 A CN102693248 A CN 102693248A CN 2011100933382 A CN2011100933382 A CN 2011100933382A CN 201110093338 A CN201110093338 A CN 201110093338A CN 102693248 A CN102693248 A CN 102693248A
- Authority
- CN
- China
- Prior art keywords
- label
- network information
- analysis module
- related content
- content analysis
- 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.)
- Pending
Links
Images
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses network information searching method and system. The method comprises the following steps that: a client sends a label of the network information to a related content analysis module of a server according to the currently browsed network information; the related content analysis module sends the label of the network information to a label intelligent association module; the label intelligent association module obtains all labels associated with the label of the network information from a label database, selects the label of which the association degree is greater than the preset threshold, and returns the label to the related content analysis module; the related content analysis module obtains the network information corresponding to the label from the content database according to the received label; and the related content analysis module returns the obtained network information to the client. By adopting the technical scheme of the invention, the content related to the current content can be displayed to the user to the greatest degree so as to help the user extend reading.
Description
Technical field
The present invention relates to magnanimity information retrieval technique field, relate in particular to a kind of method and system of web search information.
Background technology
On internet platform, in order to improve usage rate of the user, relevant with it content can be recommended to the user usually automatically in the website when the user browses certain content.The account form of related content has a variety of; The different service system has different techniques to realize means, its objective is when letting user's browsing content, can be extended to more contents that he possibly need; And the click that guides him to go to carry out next step is browsed; Increase the residence time of user in the website, improve clicking rate, promote website viscosity.
How with science the most reasonably means come to recommend useful relevant information to the user, its starting point of different application platforms is also different, perhaps recommends through artificial, perhaps passes through auto-associating.
To auto-associating; Comparatively universal mode is directly to carry out related content to search through certain keyword at present; For example content A comprises keyword " tourism "; Then relevant content traditional approach with content A then according to keyword " tourism " search, other is also comprised the related content of the content of " tourism " keyword as content A.
Existing related content mode can find the content that possesses same keyword with current content exactly; But be merely able to see the content that possesses identical or similar theme; Be not " related content " truly, its related expansion to content is obviously not enough, and for example we are when browsing " tourism " relevant content; The related content analysis of traditional approach possesses big limitation; Can only get access to the content that comprises " tourism " label, those contents that correlativity is but arranged with it that do not comprise " tourism " label but can not show, for example " guide ", " discounting air ticket " etc.
The existing related content that relies on the label mode to solve is too narrow, much reads under the scene, when we read a content, need not see the content of same subject, but on meaning, have the content of the degree of association.
Summary of the invention
The objective of the invention is to propose a kind of method and system of search network information, can help the user to extend reading to greatest extent with giving the user with the maximally related content displaying of current content.
For reaching this purpose, the present invention adopts following technical scheme:
A kind of method of search network information may further comprise the steps:
A, according to the network information of current browsing, client sends to the label of the said network information related content analysis module of server end;
B, related content analysis module send to label intelligent association module with the label of the said network information;
C, label intelligent association module get access to the label associated tag of all and the said network information from tag database, and select the label of the degree of association greater than predetermined threshold, return to the related content analysis module;
D, related content analysis module obtain the corresponding network information of label according to the label that receives from content data base;
E, related content analysis module return to client with the network information that obtains.
Among the step C, adopt random function, from the label associated tag of all and the said network information, select, choose probability to be directly proportional with the degree of association according to the degree of association.
In the step e, the related content analysis module is organized into preset data layout with the network information that obtains and returns to client.
A kind of system of search network information; Comprise client, related content analysis module, label intelligent association module, tag database and content data base; Client is connected with the related content analysis module, and the related content analysis module is connected with content data base with label intelligent association module respectively, and label intelligent association module is connected with tag database; Wherein
Client is used for the label of the network information is sent to the related content analysis module, and receives the network information that the related content analysis module returns;
The related content analysis module is used for the label of the said network information is sent to label intelligent association module; From label intelligent association module obtain the degree of association greater than predetermined threshold, with the label associated tag of the said network information; And from content data base, obtain the corresponding network information of label, return to client;
Label intelligent association module is used for getting access to from tag database the label associated tag of all and the said network information, and selects the label of the degree of association greater than predetermined threshold, returns to the related content analysis module;
Tag database is used for the storage tags and the degree of association each other thereof;
Content data base is used for the corresponding network information of storage tags.
Adopted technical scheme of the present invention; Relevant mining to content not only rests on the literal same or similar property of content institute corresponding label; More to rely on semantic association between label and the label to help the user and recommend related content, and, come among the relevant a large amount of labels of a label through distinctive Algorithm Analysis; Using more, reasonable manner filters out some relevant labels; Show related content with this again, thereby will give the user with the maximally related content displaying of current content to greatest extent, help the user to extend reading.
Description of drawings
Fig. 1 is the system architecture synoptic diagram of search network information in the specific embodiment of the invention.
Fig. 2 is the process flow diagram of search network information in the specific embodiment of the invention.
Embodiment
Further specify technical scheme of the present invention below in conjunction with accompanying drawing and through embodiment.
The main thought of technical scheme of the present invention is that the relevant mining to content not only rests on the literal same or similar property of content institute corresponding label; More to rely on semantic association between label and the label to help the user and recommend related content; And through distinctive Algorithm Analysis; Come among the relevant a large amount of labels of a label, usefulness more reasonable manner filters out some relevant labels, shows related content with this again.For example content A has the label of " newton "; We possibly have only " universal gravitation ", " classical mechanics " these vocabulary by the related pairing label of related content; We help in this way, and the user excavates and own institute browsing content possesses content associated in wider scope, goes to extend and reads.
So a tag database at first need be set, the label and the degree of association between any two thereof be stored wherein, by subsequent step is used.Describe below and how to set up this tag database: acquisition of information at first, each bar information setting is no less than 1 label, be used for identification information; Secondly any two labels with each bar information are divided into one group, and with two labels of each group and between corresponding relation store in the database, and count value is set each group label occurrence number in the database is counted.The number of times of this appearance is exactly the degree of association of two labels.
Fig. 1 is the system architecture synoptic diagram of search network information in the specific embodiment of the invention.As shown in Figure 1, this system comprises client 101, related content analysis module 102, label intelligent association module 103, tag database 104 and content data base 105.
Client is connected with the related content analysis module, and the related content analysis module is connected with content data base with label intelligent association module respectively, and label intelligent association module is connected with tag database.
Client sends to the related content analysis module with the label of the network information; And receive the network information that the related content analysis module returns; The related content analysis module sends to label intelligent association module with the label of the said network information, from label intelligent association module obtain the degree of association greater than predetermined threshold, with the label associated tag of the said network information, and from content data base, obtain the corresponding network information of label; Return to client; Label intelligent association module gets access to the label associated tag of all and the said network information from tag database, and selects the label of the degree of association greater than predetermined threshold, returns to the related content analysis module; The tag database storage tags and the degree of association each other thereof, the network information that the content database stores label is corresponding.
Fig. 2 is the process flow diagram of search network information in the specific embodiment of the invention.As shown in Figure 2, this flow process may further comprise the steps:
Step 201, according to the network information of current browsing, client sends to the label of the network information related content analysis module of server end.
Step 202, related content analysis module send to label intelligent association module with the label of the network information.
Step 203, label intelligent association module get access to the label associated tag of all and the network information from tag database, and select the label of the degree of association greater than predetermined threshold, return to the related content analysis module.
Under big data volume prerequisite, because the correlation tag number of any one label all can be very huge, so will limit the quantity of taking out.And even so; Still have numerous label, be subject to the total number of related content, can not show too much content; Therefore will use the further screening from these labels again of a kind of reasonable manner, and the label that filters out the most at last returns to analysis module.
Therefore adopt random function, from the label associated tag of all and the network information, select, choose probability to be directly proportional with the degree of association according to the degree of association.For example table 1 has shown label A, correlation tag and both degrees of association.
Table 1
| Tag name | The respective labels name | Degree of association weight |
| Label A | Label 1 | 100 |
| Label A | Label 2 | 98 |
| Label A | Label 3 | 89 |
| Label A | …… | …… |
| Label A | Label n | 40 |
| Label A | Label m | 35 |
In theory, label 1 to m all possesses the degree of association with label A, but iff simply takes out label 1; Tend to bring the illusion in the experience---the subject content of browsing label A; The related content that obtains all is the theme of label 1 but, in this embodiment, adopts the particular random function to carry out association and reads; All relevant labels of this random function random screening; Degree of association weights are big more, and the probability that this quilt screens is big more, and finally return to the related content analysis module by these labels and be used to carry out next step operation.
Step 204, related content analysis module obtain the corresponding network information of label according to the label that receives from content data base.
Step 205, related content analysis module are organized into preset data layout with the network information that obtains and return to client.
The above; Be merely the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, anyly is familiar with this technological people in the technical scope that the present invention disclosed; The variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claim.
Claims (4)
1. the method for a search network information is characterized in that, may further comprise the steps:
A, according to the network information of current browsing, client sends to the label of the said network information related content analysis module of server end;
B, related content analysis module send to label intelligent association module with the label of the said network information;
C, label intelligent association module get access to the label associated tag of all and the said network information from tag database, and select the label of the degree of association greater than predetermined threshold, return to the related content analysis module;
D, related content analysis module obtain the corresponding network information of label according to the label that receives from content data base;
E, related content analysis module return to client with the network information that obtains.
2. the method for a kind of search network information according to claim 1 is characterized in that, among the step C, adopts random function, selects from the label associated tag of all and the said network information according to the degree of association, chooses probability to be directly proportional with the degree of association.
3. the method for a kind of search network information according to claim 1 is characterized in that, in the step e, the related content analysis module is organized into preset data layout with the network information that obtains and returns to client.
4. the system of a search network information; It is characterized in that comprise client, related content analysis module, label intelligent association module, tag database and content data base, client is connected with the related content analysis module; The related content analysis module is connected with content data base with label intelligent association module respectively; Label intelligent association module is connected with tag database, wherein
Client is used for the label of the network information is sent to the related content analysis module, and receives the network information that the related content analysis module returns;
The related content analysis module is used for the label of the said network information is sent to label intelligent association module; From label intelligent association module obtain the degree of association greater than predetermined threshold, with the label associated tag of the said network information; And from content data base, obtain the corresponding network information of label, return to client;
Label intelligent association module is used for getting access to from tag database the label associated tag of all and the said network information, and selects the label of the degree of association greater than predetermined threshold, returns to the related content analysis module;
Tag database is used for the storage tags and the degree of association each other thereof;
Content data base is used for the corresponding network information of storage tags.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011100933382A CN102693248A (en) | 2011-04-14 | 2011-04-14 | Network information searching method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011100933382A CN102693248A (en) | 2011-04-14 | 2011-04-14 | Network information searching method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102693248A true CN102693248A (en) | 2012-09-26 |
Family
ID=46858705
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011100933382A Pending CN102693248A (en) | 2011-04-14 | 2011-04-14 | Network information searching method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102693248A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103870461A (en) * | 2012-12-10 | 2014-06-18 | 腾讯科技（深圳）有限公司 | Topic recommendation method, device and server |
| CN104537115A (en) * | 2015-01-21 | 2015-04-22 | 北京字节跳动科技有限公司 | Method and device for exploring user interests |
| CN106250557A (en) * | 2016-08-16 | 2016-12-21 | 青岛海信传媒网络技术有限公司 | The recommendation method and device of application |
| CN106888146A (en) * | 2015-12-15 | 2017-06-23 | 上海帅醒信息科技有限公司 | Information distribution and evaluation system based on label |
| CN108446345A (en) * | 2018-03-07 | 2018-08-24 | 维沃移动通信有限公司 | A kind of data search method and mobile terminal |
| CN108829800A (en) * | 2018-05-29 | 2018-11-16 | 努比亚技术有限公司 | A kind of search data processing method, equipment and computer readable storage medium |
| CN109925678A (en) * | 2019-03-01 | 2019-06-25 | 北京七鑫易维信息技术有限公司 | A kind of training method based on eye movement tracer technique, training device and equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101547162A (en) * | 2008-03-28 | 2009-09-30 | 国际商业机器公司 | Method and device for tagging user based on user state information |
| CN101639857A (en) * | 2009-04-30 | 2010-02-03 | 腾讯科技（深圳）有限公司 | Method, device and system for establishing knowledge questioning and answering sharing platform |
| CN101847160A (en) * | 2010-05-19 | 2010-09-29 | 深圳市五巨科技有限公司 | Method and device for pushing personalized pages to mobile terminal |
-
2011
- 2011-04-14 CN CN2011100933382A patent/CN102693248A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101547162A (en) * | 2008-03-28 | 2009-09-30 | 国际商业机器公司 | Method and device for tagging user based on user state information |
| CN101639857A (en) * | 2009-04-30 | 2010-02-03 | 腾讯科技（深圳）有限公司 | Method, device and system for establishing knowledge questioning and answering sharing platform |
| CN101847160A (en) * | 2010-05-19 | 2010-09-29 | 深圳市五巨科技有限公司 | Method and device for pushing personalized pages to mobile terminal |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103870461A (en) * | 2012-12-10 | 2014-06-18 | 腾讯科技（深圳）有限公司 | Topic recommendation method, device and server |
| WO2014090007A1 (en) * | 2012-12-10 | 2014-06-19 | 腾讯科技（深圳）有限公司 | Method, device and server for acquiring recommended theme |
| US10169449B2 (en) | 2012-12-10 | 2019-01-01 | Tencent Technology (Shenzhen) Company Limited | Method, apparatus, and server for acquiring recommended topic |
| CN104537115A (en) * | 2015-01-21 | 2015-04-22 | 北京字节跳动科技有限公司 | Method and device for exploring user interests |
| CN104537115B (en) * | 2015-01-21 | 2019-07-16 | 北京字节跳动科技有限公司 | The heuristic approach and device of user interest |
| CN106888146A (en) * | 2015-12-15 | 2017-06-23 | 上海帅醒信息科技有限公司 | Information distribution and evaluation system based on label |
| CN106250557A (en) * | 2016-08-16 | 2016-12-21 | 青岛海信传媒网络技术有限公司 | The recommendation method and device of application |
| CN108446345A (en) * | 2018-03-07 | 2018-08-24 | 维沃移动通信有限公司 | A kind of data search method and mobile terminal |
| CN108446345B (en) * | 2018-03-07 | 2021-11-09 | 维沃移动通信有限公司 | Data searching method and mobile terminal |
| CN108829800A (en) * | 2018-05-29 | 2018-11-16 | 努比亚技术有限公司 | A kind of search data processing method, equipment and computer readable storage medium |
| CN108829800B (en) * | 2018-05-29 | 2021-11-16 | 努比亚技术有限公司 | Search data processing method and device and computer readable storage medium |
| CN109925678A (en) * | 2019-03-01 | 2019-06-25 | 北京七鑫易维信息技术有限公司 | A kind of training method based on eye movement tracer technique, training device and equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102693248A (en) | Network information searching method and system | |
| KR101514588B1 (en) | System and method for providing contextual actions on a search results page | |
| CN102279851B (en) | Intelligent navigation method, device and system | |
| JP4637969B1 (en) | Properly understand the intent of web pages and user preferences, and recommend the best information in real time | |
| CN102929928B (en) | Multidimensional-similarity-based personalized news recommendation method | |
| CN101542482B (en) | Bookmarks and ranking | |
| CN104484431B (en) | A kind of multi-source Personalize News webpage recommending method based on domain body | |
| CN104102639B (en) | Popularization triggering method based on text classification and device | |
| US20120158703A1 (en) | Search lexicon expansion | |
| CN105930469A (en) | Hadoop-based individualized tourism recommendation system and method | |
| CN103186550A (en) | Method and system for generating video-related video list | |
| CN105718184A (en) | Data processing method and apparatus | |
| CN104462336A (en) | Information pushing method and device | |
| CN102446225A (en) | Real-time search method, device and system | |
| CN102708174A (en) | Method and device for displaying rich media information in browser | |
| CN102314461B (en) | Navigation prompt method and system | |
| CN104090963A (en) | Search information recommendation method and device | |
| CN102236719A (en) | Page search engine based on page classification and quick search method | |
| CN106293119A (en) | A kind of method and apparatus carrying out information recommendation in input method | |
| CN103064852A (en) | Website statistical information processing method and website statistical information processing system | |
| CN109241451A (en) | A kind of content combined recommendation method, apparatus and readable storage medium storing program for executing | |
| CN111191112A (en) | Electronic reading data processing method, device and storage medium | |
| CN104050243A (en) | Network searching method and system combined with searching and social contact | |
| CN102419773B (en) | Method, device and equipment used for sequencing resource items | |
| CN103294670A (en) | Searching method and system based on word list |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20120926 |