CN107169825A - A kind of user preference analysis method and system - Google Patents
A kind of user preference analysis method and system Download PDFInfo
- Publication number
- CN107169825A CN107169825A CN201710319067.5A CN201710319067A CN107169825A CN 107169825 A CN107169825 A CN 107169825A CN 201710319067 A CN201710319067 A CN 201710319067A CN 107169825 A CN107169825 A CN 107169825A
- Authority
- CN
- China
- Prior art keywords
- user
- information
- classifying rules
- initial information
- business tine
- 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
Classifications
-
- 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
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
- G06F16/355—Class or cluster creation or modification
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Accounting & Taxation (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Finance (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a kind of user preference analysis method, comprise the following steps：The behavior that accesses based on user obtains the initial information that the user accesses；Classification processing is carried out to the Web content involved by user described in the initial information；The frequency is browsed to the user involved by user described in initial information to arrange；The preference of the user is scored according to the content information and frequency information, the preference information of the user is drawn.Present invention also offers a kind of user preference analysis system, including：Initial information acquisition module, content information sort module, frequency message ordering module and grading module, the present invention is by above technical scheme, and the complexity of its classifying content algorithm is relatively low；In terms of resource requirement and promoting feasibility, the technical program is based on simple system architecture, very low to hardware resource requirements, is easily promoted in various regions.
Description
Technical field
The present invention relates to computer network data technical field, particularly a kind of user preference analysis method and system.
Background technology
With continuing to develop for technology, network social intercourse has been increasingly becoming a kind of new social mode, and network social intercourse is from initial
Email various social network sites (SNS, SocialNetwork Sites) till now, such as shopping, friend-making sites.
Under normal circumstances, social network sites need user to be applied for the registration of on corresponding website, and fill in the personal information of correlation, from
And obtain personal account.When User logs in social network sites, personal account and relevant information become for website or other people recognize
The primary identity of user identity.
In some social network sites, in order to preferably promote site information, the seller for class website of for example doing shopping enters to commodity
Row is promoted, it will usually carry out recommendation displaying to other commodity in the commodity page of a certain seller.And such recommendation exhibition information
Commending contents generally with reference to interested to user, then can greatly improve the usage experience of user.Therefore a kind of use of design is needed badly
Family preference analysis method and system.
The content of the invention
In view of the above-mentioned problems existing in the prior art, it is an object of the invention to provide a kind of user preference analysis method and
System.
The invention provides a kind of user preference analysis method, comprise the following steps：
The behavior that accesses based on user obtains the initial information that the user accesses；
Classification processing is carried out to the Web content involved by user described in the initial information, content information is obtained；
The frequency is browsed to the user involved by user described in initial information to arrange, and obtains frequency information；
The preference of the user is scored according to the content information and frequency information, the preference of the user is drawn
Information.
Preferably, the initial information that the access behavior acquisition user based on user accesses includes：
The basic data that the user accesses is obtained from server according to the access behavior of the user；
The business tine that the user accesses is obtained according to the basic data, and according to the increase of the basic data,
The business tine is extended, the initial information is generated.
Preferably, the Web content to involved by user in the initial information, which carries out classification processing, includes：
The behavior that accesses based on user obtains the initial information that the user accesses；
Judge whether each business tine has default first classifying rules in the initial information, and obtain a judgement knot
Really；
It is the business tine with first classifying rules to the judged result, according to first classifying rules pair
The business tine is classified；
It is the business tine without first classifying rules to the judged result, according to the second classifying rules to institute
Business tine is stated to be classified；
The preference of the user is scored according to the content information and frequency information, the preference of the user is drawn
Information.
Preferably, second classifying rules is the classifying rules built temporarily, and the method reference of the structure is described
The construction method of first classifying rules.
Preferably, the construction method of first classifying rules uses URL matching methods or text matches method, and to described
The granularity of classification of Web content produced by after business tine classification is controlled within intended level.
Present invention also offers a kind of user preference analysis system, including：
Initial information acquisition module, the initial information that the user accesses is obtained for the behavior that accesses based on user；
Content information sort module, for classifying to the Web content involved by user described in the initial information
Processing, obtains content information；
Frequency message ordering module, it is whole for browsing frequency progress to the user involved by user described in initial information
Reason, obtains frequency information；
Grading module, for being scored according to the content information and frequency information the preference of the user, draws
The preference information of the user.
Preferably, initial information acquisition module includes：
Basic data acquiring unit, is accessed for obtaining the user from server according to the access behavior of the user
Basic data；
Expanding element, for obtaining the business tine that the user accesses according to the basic data, and according to the base
The increase of plinth data, is extended to the business tine, generates the initial information.
Preferably, the content information sort module includes：
Including judging unit, for judging whether each business tine has the default first classification in the initial information
Rule, and obtain a judged result；
Taxon, for being the business tine with first classifying rules to the judged result, according to described
First classifying rules is classified to the business tine；
It is the business tine without first classifying rules to the judged result, according to the second classifying rules to institute
Business tine is stated to be classified.
Preferably, the second classifying rules constructed by the taxon is the classifying rules that builds temporarily, and the structure
Construction method of the method built with reference to first classifying rules.
Preferably, the construction method of the first classifying rules constructed by the taxon uses URL matching methods or text
Matching method, and the granularity of classification of Web content produced after business tine classification is controlled within intended level.
In summary, the present invention has advantages below：
The present invention positions the inclined of user by above technical scheme by integrating with the content of heterogeneity business is associated
Good, its accuracy requirement to classifying content is relatively low, therefore the complexity of its classifying content algorithm is relatively low；In resource requirement and
In terms of promoting feasibility, the technical program is based on simple system architecture, very low to hardware resource requirements, is easily pushed away in various regions
Extensively.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the present embodiment preference analysis method；
Fig. 2 is the structured flowchart of the preference analysis system of the present embodiment.
Embodiment
The present invention is made with reference to embodiment and accompanying drawing further in detail, intactly to illustrate.
As shown in Figure 1-2, a kind of user preference analysis method, comprises the following steps：
The behavior that accesses based on user obtains the initial information that the user accesses；
Classification processing is carried out to the Web content involved by user described in the initial information, content information is obtained；
The frequency is browsed to the user involved by user described in initial information to arrange, and obtains frequency information；
The preference of the user is scored according to the content information and frequency information, the preference of the user is drawn
Information.
The initial information that the access behavior based on user obtains user's access includes：
The basic data that the user accesses is obtained from server according to the access behavior of the user；
The business tine that the user accesses is obtained according to the basic data, and according to the increase of the basic data,
The business tine is extended, the initial information is generated.
The Web content to involved by user in the initial information, which carries out classification processing, to be included：
The behavior that accesses based on user obtains the initial information that the user accesses；
Judge whether each business tine has default first classifying rules in the initial information, and obtain a judgement knot
Really；
It is the business tine with first classifying rules to the judged result, according to first classifying rules pair
The business tine is classified；
It is the business tine without first classifying rules to the judged result, according to the second classifying rules to institute
Business tine is stated to be classified；
The preference of the user is scored according to the content information and frequency information, the preference of the user is drawn
Information.
Second classifying rules is the classifying rules that builds temporarily, and the structure method with reference to the described first classification
The construction method of rule.
The construction method of first classifying rules uses URL matching methods or text matches method, and in the business
The granularity of classification for holding the Web content produced by after classification is controlled within intended level.
Present invention also offers a kind of user preference analysis system, including：
Initial information acquisition module, the initial information that the user accesses is obtained for the behavior that accesses based on user；
Content information sort module, for classifying to the Web content involved by user described in the initial information
Processing, obtains content information；
Frequency message ordering module, it is whole for browsing frequency progress to the user involved by user described in initial information
Reason, obtains frequency information；
Grading module, for being scored according to the content information and frequency information the preference of the user, draws
The preference information of the user.
Initial information acquisition module includes：
Basic data acquiring unit, is accessed for obtaining the user from server according to the access behavior of the user
Basic data；
Expanding element, for obtaining the business tine that the user accesses according to the basic data, and according to the base
The increase of plinth data, is extended to the business tine, generates the initial information.
The content information sort module includes：
Including judging unit, for judging whether each business tine has the default first classification in the initial information
Rule, and obtain a judged result；
Taxon, for being the business tine with first classifying rules to the judged result, according to described
First classifying rules is classified to the business tine；
It is the business tine without first classifying rules to the judged result, according to the second classifying rules to institute
Business tine is stated to be classified.
The second classifying rules constructed by the taxon is the classifying rules built temporarily, and the method for the structure
With reference to the construction method of first classifying rules.
The construction method of the first classifying rules constructed by the taxon uses URL matching methods or text matches method,
And the granularity of classification of the Web content produced by after classifying to the business tine is controlled within intended level
The above embodiment of the present invention is only that explanation technical solution of the present invention is used simultaneously, only the row of technical solution of the present invention
Lift, the technical scheme and its protection domain being not intended to limit the invention.Using equivalent technologies mean, equivalent apparatus etc. to this hair
The improvement of technical scheme disclosed in bright claims and specification is considered to be without departing from claims of the present invention
And the scope disclosed in specification.
Claims (10)
1. a kind of user preference analysis method, it is characterised in that comprise the following steps：
The behavior that accesses based on user obtains the initial information that the user accesses；
Classification processing is carried out to the Web content involved by user described in the initial information, content information is obtained；
The frequency is browsed to the user involved by user described in initial information to arrange, and obtains frequency information；
The preference of the user is scored according to the content information and frequency information, the preference letter of the user is drawn
Breath.
2. user preference analysis method as claimed in claim 1, it is characterised in that the access behavior based on user is obtained
The initial information that the user accesses includes：
The basic data that the user accesses is obtained from server according to the access behavior of the user；
The business tine that the user accesses is obtained according to the basic data, and according to the increase of the basic data, to institute
State business tine to be extended, generate the initial information.
3. user preference analysis method as claimed in claim 1, it is characterised in that
The Web content to involved by user in the initial information, which carries out classification processing, to be included：
The behavior that accesses based on user obtains the initial information that the user accesses；
Judge whether each business tine has default first classifying rules in the initial information, and obtain a judged result；
It is the business tine with first classifying rules to the judged result, according to first classifying rules to described
Business tine is classified；
It is the business tine without first classifying rules to the judged result, according to the second classifying rules to the industry
Business content is classified；
The preference of the user is scored according to the content information and frequency information, the preference letter of the user is drawn
Breath.
4. user preference analysis method as claimed in claim 3, it is characterised in that
Second classifying rules is the classifying rules that builds temporarily, and the structure method with reference to first classifying rules
Construction method.
5. user preference analysis method as claimed in claim 4, it is characterised in that the construction method of first classifying rules
Using URL matching methods or text matches method, and to the granularity of classification of Web content produced after business tine classification
Control is within intended level.
6. a kind of user preference analysis system, it is characterised in that including：
Initial information acquisition module, the initial information that the user accesses is obtained for the behavior that accesses based on user；
Content information sort module, for being carried out to the Web content involved by user described in the initial information at classification
Reason, obtains content information；
Frequency message ordering module, arranges for browsing the frequency to the user involved by user described in initial information, obtains
To frequency information；
Grading module, for being scored according to the content information and frequency information the preference of the user, draws described
The preference information of user.
7. as claim 6 user preference analysis system, it is characterised in that initial information acquisition module includes：
Basic data acquiring unit, for obtaining the base that the user accesses from server according to the access behavior of the user
Plinth data；
Expanding element, for obtaining the business tine that the user accesses according to the basic data, and according to the basic number
According to increase, the business tine is extended, the initial information is generated.
8. as claim 7 user preference analysis system, it is characterised in that the content information sort module includes：
Including judging unit, for judging whether each business tine has default first classification gauge in the initial information
Then, and a judged result；
Taxon, for being the business tine with first classifying rules to the judged result, according to described first
Classifying rules is classified to the business tine；
It is the business tine without first classifying rules to the judged result, according to the second classifying rules to the industry
Business content is classified.
9. as claim 8 user preference analysis system, it is characterised in that constructed by the taxon second classification
Rule is the classifying rules that builds temporarily, and the structure method with reference to first classifying rules construction method.
10. as claim 9 user preference analysis system, it is characterised in that first point constructed by the taxon
The construction method of rule-like uses URL matching methods or text matches method, and to net produced after business tine classification
The granularity of classification of network content is controlled within intended level.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710319067.5A CN107169825A (en) | 2017-05-08 | 2017-05-08 | A kind of user preference analysis method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710319067.5A CN107169825A (en) | 2017-05-08 | 2017-05-08 | A kind of user preference analysis method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107169825A true CN107169825A (en) | 2017-09-15 |
Family
ID=59813633
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710319067.5A Pending CN107169825A (en) | 2017-05-08 | 2017-05-08 | A kind of user preference analysis method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107169825A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103544188A (en) * | 2012-07-17 | 2014-01-29 | 中国移动通信集团广东有限公司 | Method and device for pushing mobile internet content based on user preference |
| CN105022729A (en) * | 2014-04-15 | 2015-11-04 | 中国移动通信集团河北有限公司 | User preference determination method and device |
| CN105894332A (en) * | 2016-04-22 | 2016-08-24 | 深圳市永兴元科技有限公司 | Commodity recommendation method, device and system based on user behavior analysis |
-
2017
- 2017-05-08 CN CN201710319067.5A patent/CN107169825A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103544188A (en) * | 2012-07-17 | 2014-01-29 | 中国移动通信集团广东有限公司 | Method and device for pushing mobile internet content based on user preference |
| CN105022729A (en) * | 2014-04-15 | 2015-11-04 | 中国移动通信集团河北有限公司 | User preference determination method and device |
| CN105894332A (en) * | 2016-04-22 | 2016-08-24 | 深圳市永兴元科技有限公司 | Commodity recommendation method, device and system based on user behavior analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10097623B2 (en) | Method and device for displaying information flows in social network, and server | |
| JP6208317B2 (en) | Static ranking for search queries in online social networks | |
| US20190294642A1 (en) | Website fingerprinting | |
| JP6377807B2 (en) | Rewriting search queries in online social networks | |
| US20140095308A1 (en) | Advertisement distribution apparatus and advertisement distribution method | |
| US8498895B2 (en) | Browser based user identification | |
| JP6023129B2 (en) | Extraction apparatus, extraction method, and extraction program | |
| US20180365710A1 (en) | Website interest detector | |
| US11275748B2 (en) | Influence score of a social media domain | |
| US11907644B2 (en) | Detecting compatible layouts for content-based native ads | |
| TWI525456B (en) | Choose font, font determination, recommendation, generation method and device | |
| US20140173031A1 (en) | Information providing apparatus, information providing method, and network system | |
| CN105701694A (en) | Method and system for creating electronic store | |
| CN106033450A (en) | Method and device for blocking advertisement, and browser | |
| US20140207770A1 (en) | System and Method for Identifying Documents | |
| KR102643311B1 (en) | Marketer and advertisement request information management system | |
| CN110197375A (en) | A kind of similar users recognition methods, device, similar users identification equipment and medium | |
| US20160124580A1 (en) | Method and system for providing content with a user interface | |
| CN111882224A (en) | Method and device for classifying consumption scenes | |
| CN104462257B (en) | The method and apparatus of page information among a kind of verification | |
| JP6680472B2 (en) | Information processing apparatus, information processing method, and information processing program | |
| JP2020129239A (en) | Post Analysis System, Post Analysis Device, and Post Analysis Method | |
| JP2016177620A (en) | Information processing device, information processing method, information processing program | |
| CN107169825A (en) | A kind of user preference analysis method and system | |
| JP4550939B1 (en) | Information propagation path identification device, information propagation path identification method, information propagation path identification program |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170915 |
|
| RJ01 | Rejection of invention patent application after publication |