CN102955805A - Method and system for processing recommendation data of website information - Google Patents
Method and system for processing recommendation data of website information Download PDFInfo
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- CN102955805A CN102955805A CN2011102478669A CN201110247866A CN102955805A CN 102955805 A CN102955805 A CN 102955805A CN 2011102478669 A CN2011102478669 A CN 2011102478669A CN 201110247866 A CN201110247866 A CN 201110247866A CN 102955805 A CN102955805 A CN 102955805A
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Abstract
The invention provides a method for processing recommendation data of website information. The method includes acquiring operation of a recommender for recommending the website information and recording information of the recommender in a user record of received recommendation; determining a recommendation link of the website information according to the information of the recommender in the user record; and counting the recommendation data in the website information according to user information of various users in the recommendation link. The invention further provides a system for processing the recommendation data of the website information. The system is used for implementing the method. The method and the system for processing the recommendation data of the website information have the advantages that the recommendation data of the website information can be counted, and the statistical accuracy of the data is guaranteed.
Description
Technical field
The application relates to the computer network data technical field, particularly relates to a kind of site information recommending data disposal route and system.
Background technology
Along with the development of technology, network social intercourse becomes a kind of new social mode gradually, and network social intercourse develops into present various social network sites (SNS, Social Network Sites) from initial Email.Generally, social network sites needs the user to apply for the registration of in corresponding website, and fills in relevant personal information, thereby obtains individual account.When the user logined social network sites, individual account and relevant information just become the website or other people identify the main sign of user identity.
In order to promote the information in the social network sites, social network sites always wishes that the user can recommend other users with the site information of oneself accessing, such as video, commodity etc.In order to improve user's enthusiasm, social network sites also can arrange some and reward to encourage to recommend.Such as present a lot of group buying websites, if when stipulating that a certain user gives other users with the product successful referral, can obtain the profit of returning of certain amount of money.At the selling film ticket, A tells B with this link by QQ, msn or other modes such as certain group buying websites, and then B connects film ticket of purchase according to this, and A will obtain this website and return profit so, can be used for it and consume in this website.Yet this kind way of recommendation only limits to two person-to-person mutual recommendations, if product is through multistage recommendation, also can only get access to last two person-to-person recommendation informations.When the website when carrying out follow-up work, for example, when wishing the recommending data of all site informations added up to obtain relevant information, need to search a large amount of data, increase timing statistics, and, because information recording/ is imperfect, statistics also error can occur.
Summary of the invention
The application's technical matters to be solved provides a kind of site information recommending data disposal route and system, can add up and guarantee to the recommending data of site information the accuracy of statistics.
In order to address the above problem, the application discloses a kind of site information recommending data disposal route, may further comprise the steps:
Obtain the operation of nominator recommended website information, and in receiving the user record of recommending, record nominator's information;
Determine the recommendation chain of site information according to the nominator's information in the user record;
According to the user profile of recommending each user in the chain, the recommending data of site information is added up.
Further, the described nominator's information that records in receiving the user record of recommending comprises:
When the user accesses some websites information for the first time, judge to have or not the nominator, if do not have, then the nominator's information recording/ with this user is empty, if having, then records nominator's information;
When this site information of user's subsequent access, do not change its original nominator's information.
Further, described record nominator information comprises:
With current nominator's information recording/in the user record of its recommended.
Further, the recommendation chain of described definite site information comprises:
Choose a user, determine step by step the nominator forward, until the nominator is the user of active access websites information.
Further, described record nominator information comprises:
Will be at the recommendation transmission of information before the current nominator and current nominator's information recording/in the user record in its recommended.
Further, the recommendation chain of described definite site information comprises:
Choose a user, the recommendation transmission of information from this user's user record obtains the recommendation chain.
Further, the operation of the described nominator of obtaining recommended website information comprises:
Obtain the nominator and copy the corresponding operation that links of site information, nominator's information is added in the link, from described link, obtain this nominator's information; Or
Obtain the nominator and click the operation of corresponding button in the website, generate the recommendation message that includes nominator's information, from described recommendation message, obtain this nominator's information.
Further, described user profile according to recommending each user in the chain, the recommending data of site information added up comprise:
Obtain the feedback information of recommending each user in the chain, the user that will have identical feedback information is divided into a class; Or
Obtain the positional information of recommending each user in the chain, according to each user the feedback information of site information is added up site information in the degree that is accepted in each place.
Further, the described feedback information of recommending each user in the chain that obtains, the user that will have identical feedback is divided into a class and also comprises afterwards:
Obtain all types of user preference according to classification results;
Choose all types of user according to user preference and wish that the site information that obtains shows it.
Further, described method also comprises:
Obtain and recommend in the chain each user to the feedback information of site information;
Determine effectively to recommend chain and effective nominator according to field feedback.
In order to address the above problem, disclosed herein as well is a kind of site information commending system, comprising:
Nominator's acquisition of information module for the operation of obtaining nominator recommended website information, and records nominator's information in receiving the user record of recommending;
Recommend the chain determination module, be used for determining according to nominator's information of user record the recommendation chain of site information;
Statistical module is used for according to the user profile of recommending each user of chain the recommending data of site information being added up.
Further, described nominator's acquisition of information module comprises:
Nominator's information recording unit is used for when the user accesses some websites information for the first time, judges to have or not the nominator, if do not have, then the nominator's information recording/ with this user is empty, if having, then records nominator's information; When this site information of user's subsequent access, do not change its original nominator's information.
Further, described nominator's information recording unit comprises:
Current nominator's information recording/subelement is used for current nominator's the information recording/user record in its recommended.
Further, described recommendation chain determination module comprises:
First searches the unit, is used for receiving the user who recommends according to each user record from last and determines step by step the nominator forward, until the nominator is the user of active access websites information.
Further, described nominator's information recording unit comprises:
Recommend the transmission of information record cell, be used for the recommendation transmission of information before current nominator and the current nominator's information recording/user record in its recommended.
Further, described recommendation chain determination module comprises:
Second searches the unit, obtains for the recommendation transmission of information that receives the user record of recommending from last and recommends chain and nominator.
Further, described statistical module comprises:
Taxon is used for obtaining the feedback information of recommending each user of chain, and the user that will have identical feedback is divided into a class; Or
Location information acquiring unit is used for obtaining the positional information of recommending each user of chain, according to each user the feedback information of site information is added up site information in the degree that is accepted in each place.
Further, described system also comprises:
Effectively nominator's determination module is used for obtaining each user of recommendation chain to the feedback information of site information, and determines effectively to recommend chain and effective nominator according to field feedback.
Compared with prior art, the application comprises following advantage:
The application's site information recommending data disposal route and system pass through nominator's information recording/in receiving the user record of recommending, can be when follow-up data be added up, selected user, as the user who recommended, and determine forward step by step the nominator, just can obtain the recommendation chain of site information, and carry out the statistics of recommending data according to the recommendation chain that obtains, thereby realize a large amount of recommending datas of site information are processed, and, can find each user who participates in recommendation by the mode of recommending chain, thereby guarantee the accuracy of statistics, because the application carries out statistical study on the basis of recommending chain, rather than the user profile of all users in the website carried out statistical study, alleviate the data volume of statistical study, saved the workload of web station system data analysis, improved the efficient of statistical study.
Secondly, to recommend the user who provides identical feedback information in the chain to be divided into a class, to determine user preference, the site information that when subsequent operation, can provide its hope to obtain to the user for user preference, guarantee the accuracy that site information provides, the number of times of initiatively searching to reduce the user, thereby the burden of minimizing Website server.
In addition, by the recommendation chain is analyzed, obtain each user's positional information, and judge that according to user's feedback information site information is in the degree that is accepted in each place, thereby can be so that determine the emphasis of some site information information issue, save the process that the website is investigated and analysed again, avoided system resource waste.
Certainly, arbitrary product of enforcement the application not necessarily needs to reach simultaneously above-described all advantages.
Description of drawings
Fig. 1 is the process flow diagram of the application's site information recommending data disposal route embodiment one;
Fig. 2 is the process flow diagram of the nominator's information recording method in the application's site information recommending data disposal route shown in Figure 1;
Fig. 3 is the process flow diagram of the application's site information recommending data disposal route embodiment two;
Fig. 4 is the structural representation of the application's site information commending system embodiment one;
Fig. 5 is the structural representation of the application's site information commending system embodiment two.
Embodiment
For above-mentioned purpose, the feature and advantage that make the application can become apparent more, below in conjunction with the drawings and specific embodiments the application is described in further detail.
With reference to Fig. 1, a kind of site information recommending data disposal route embodiment one of the application is shown, may further comprise the steps:
Site information can be a certain commodity on the website, a certain video or hot news etc.; when the website wishes this site information promoted; usually can increase recommended links at site information; thereby make things convenient for the user after browsing or find this site information, this site information is recommended other users.
Can be by copying the link of this site information when the nominator recommends site information, and pass to other users by modes such as instant messenger or mails.In order to record nominator's information; usually can be (such as URL (URL(uniform resource locator) in link; the information of Uniform Resource Locator)) adding this nominator; in the time need in receiving the user record of recommending, recording nominator's information, then directly can from this link, obtain.Wherein, nominator's information can be the user number of registration (registration ID) of user on the website, also can be the IP address of the employed user terminal of user or the machine code of user terminal etc., nominator's information can directly be recorded among the cookie that receives the user who recommends, also can be stored in the server, when needed, then can directly from user cookie or server, read.
In addition, the website also can preset button, and the nominator is by after clicking corresponding button, and the website is automatic generating recommendations message just, and nominator's information is added in the recommendation message.This recommendation message can pass to by the mode of instant messaging other users, also can directly be published in the social network sites, when other presentees have clicked this recommendation message, just records nominator's information in receiving the user record of recommending.
The frequent modification to data that causes because of duplicate record for fear of nominator's information, occupying system resources and cause data redundancy, when carrying out nominator's information recording/, nominator's information when recording user is accessed this site information for the first time, if and follow-up this user is not because the recommendation of accepting other nominators when this site information is conducted interviews, then can be carried out record.
With reference to Fig. 2, concrete can realize in the following way:
When D1, user access some websites information for the first time, judge to have or not the nominator, if do not have, then the nominator's information recording/ with this user is empty, if having, then records nominator's information.
Wherein, judge to have or not the nominator, can determine by whether nominator's information is arranged in this user profile, if nominator's information is arranged, then thinking has the nominator, otherwise, then do not have.
D2 when this site information of user's subsequent access, does not change its original nominator's information.
During this site information of user's subsequent access, no matter whether recommend or own initiatively access through others, can not change its original recommendation information.For example, when the user accesses some websites information for the first time, do not have the nominator, at this moment, record its nominator's information for empty, even this this site information of user's subsequent access is the recommendation through others, its nominator's information still is empty.
If site information through multistage recommendation, can record every one-level nominator's information so successively.Wherein, in the user record of its recommended, namely each nominator's information only is recorded in the user record of its recommended, can reduce the data volume of record like this, thereby alleviates the burden of server with current nominator's information recording/.In addition, nominator's information also can adopt the mode record of recommending chain, to at the recommendation transmission of information before the current nominator and current nominator's information recording/in the user record in its recommended, namely receive the recommendation transmission of information of also recording the site information front in the user record of recommending in the record nominator information at each.
Step 102 is determined the recommendation chain of site information according to the nominator's information in each user record.
Determine that the recommendation chain of site information can realize in the following manner: choose a user, determine step by step the nominator forward, until the nominator be the user of active access websites information.Wherein, the user who chooses can be that any one receives the user who recommends, and for fear of repetition, identical recommendation chain only records once.For example, a site information is recommended B by A, and B recommends C, and C recommends D.If choose user B, the recommendation chain of then determining is A-＞B, and if choose D, the recommendation chain of then determining is A-＞B-＞C-＞D, so, can find out the part of A-＞B for repeating, can choose long recommendation chain and cover short recommendation chain, thereby avoid duplicating, guarantee the accuracy of statistics.
In addition, also can choose a user, the recommendation transmission of information from this user's user record directly obtains the recommendation chain.Certainly, the recommendation chain if there is repeating also can adopt aforesaid method, with long recommendation chain short recommendation chain is covered.
Step 103 according to the user profile of recommending each user in the chain, is added up the recommending data of site information.
User profile comprises that the user is to the feedback information of site information and customer position information etc.The recommending data of site information added up comprise: according to recommending the feedback information in the chain that the user is classified.The user that for example, will have an identical feedback is divided into a class.For example, in a recommendation chain A-＞B-＞C-＞D-＞E-＞F-＞G-＞H, A, D, G have bought this commodity, and all the other people just recommend, and think that then A, D, G are exactly the crowd of common interest, they are divided into a class, and the user that all the other are recommended, as, B, C, E, F, also think to have the crowd of common interest, can be divided into a class.In addition, can also add up the number of times that each user occurs and determine it to the interest of a certain site information in different recommendation chains, number of times is divided into a class in setting range.Certainly, can also come the user is classified according to other modes, this and application limit this.Can find each user who participates in recommendation by the mode of recommending chain, thereby make the statistics of recommending data more accurate.And because the embodiment of the present application is to carry out statistical study on the basis of recommending chain, rather than the user profile of all users in the website carried out statistical study, alleviate the data volume of statistical study, saved the workload of web station system data analysis, improved the efficient of statistical study.
After the user is classified, can analyze all types of user preference, thereby the site information of classifying and providing its hope to obtain to the user for the user reduces the number of times that the user initiatively searches, thereby reduce the burden with Website server of taking to site resource.
In addition, to the recommending data of site information add up also can for: obtain the positional information of recommending each user in the chain, according to each user to the feedback information statistics site information of the site information degree that is accepted in each place.For example, user A recommends certain commodity to the friend of its U.S., but unmanned the purchase, be on the contrary the friend of A this commercial product recommending to the friend in one Europe, generation is sold fast, thereby can infer that these commodity are that Europe is more welcome, so later on can be with Europe as the main promoting region with these commodity.
In addition, can also will recommend chain to be presented in each nominator's the accession page, understand own position in recommending chain thereby be convenient to the user.Further, the user who can also be in recommending chain site information be provided the expection feedback carries out mark, and the recommendation chain behind the mark is presented in each nominator's the accession page, understands the user profile that has common hobby with it thereby be convenient to the user.For example, take the user A of social network sites as example, there is the user of common interest to comprise 3 parts with A: the direct good friend who bought the A of these commodity; Buy the user of these type of commodity at the recommendation chain relevant with A, represent good friend's good friend; And other bought the user of these commodity, represented other users.
The application's site information recommending data disposal route and system pass through nominator's information recording/in receiving the user record of recommending, can be when follow-up data be added up, selected user, as the user who recommended, and determine forward step by step the nominator, just can obtain the recommendation chain of site information, and carry out the statistics of recommending data according to the recommendation chain that obtains, thereby realize a large amount of recommending datas of site information are processed, and, can find each user who participates in recommendation by the mode of recommending chain, thereby guarantee the accuracy of statistics.
Preferably, with reference to Fig. 3, the application's site information recommending data disposal route embodiment two is shown, further comprising the steps of after step 103:
Step 201 determines effectively to recommend chain and effective nominator according to the field feedback in the recommendation chain that obtains.
If a certain user has made the feedback of expection to a certain site information through other users' recommendation, think so this time to be recommended as effective recommendation.For example, site information is commodity, the website wishes that the user buys this commodity, the user buys the feedback that these commodity then think site information has been made expection so, if site information is video, the website wishes that the user clicks and browses this video, and the user clicks and browses the feedback that this video then thinks site information has been made expection so.Forming so the recommendation chain of effectively recommending is effectively to recommend chain, and effectively recommending all nominators in the chain is effective nominator.
At this moment, according to aforesaid two kinds of nominator's information recording/modes, effectively recommend chain and effective nominator to obtain by following two kinds of methods.If each nominator's information only is recorded in the user record of its recommended, so can be by the mode of searching step by step, receive the user who recommends from last, namely provide the user of expection feedback, determine step by step the nominator forward, until find the initiatively user of access websites information, i.e. first nominator, the path of this search procedure is effective recommendation chain, and determined all nominators are effective nominator in the search procedure.If each receives and recommends the nominator who determines in the search procedure is effective nominator, recorded the recommendation transmission of information of front in the user record of path for the recommendation chain of described all effective nominators according to the recommendation order composition, can directly receive the user record of recommending from last so and directly obtain the recommendation chain, recommend in the transmission of information, namely recommending all users that comprise in the chain is all effective nominators, adopt this mode, can reduce inquiry times, thereby improve response speed.
For example, commodity are recommended B by A, and B recommends C, and C has recommended D, and only has C finally to buy these commodity, and so, recommend chain to be: A-＞B-＞C-＞D, effectively recommend chain to be: A-＞B-＞C, wherein, A and B are considered to effective nominator.
Further, after the step 201 of embodiment two, can also may further comprise the steps:
Set allocation rule, reward distribution to all effective nominators.
Award can preset to carry out according to the website, for example increases user integral or returns cash etc. mode.When effective nominator rewards to all, preset allocation rule, for example, each effective nominator's mean allocation or according to recommending contribution to reward step by step namely has the different resulting award ratios of people of contribution of recommending different.
In the recommendation contribution that can determine according to aforesaid effective recommendation chain each effective nominator according to contribution when rewarding step by step.Can namely effectively recommend the every one-level nominator on the chain to contribute according to recommendation according to the mode of successively decreasing step by step, the award ratio that it obtains be different.Adopt the allocation scheme of rewarding step by step can guarantee to reward the rationality of distribution.For example, E has bought a certain commodity, and the recommendation chain that finds its correspondence is A-＞B-＞C-＞D-＞E, then can determine, E is because this commodity have been bought in the recommendation of D, can think that so the recommendation contribution of D is maximum, is first order nominator, C takes second place, and is second level nominator, by that analogy.In addition, also can determine to contribute one or two larger nominators allocation proportion, follow-up nominator adopts identical ratio to distribute.This kind mode can reduce calculated amount when effectively nominator's quantity is more, thereby reduces taking system resource.For example, allocation rule is: first order nominator distributes larger ratio, and such as 50%, the second level nominator take second place, such as 30%, and the remaining remaining ratio of nominator's mean allocation.
With reference to Fig. 4, the site information commending system of the embodiment of the present application one is shown, comprise nominator's acquisition of information module 10, recommend chain determination module 20 and statistical module 30.
Nominator's acquisition of information module 10 for the operation of obtaining nominator recommended website information, and records nominator's information in receiving the user record of recommending.
Recommend chain determination module 20, be used for determining according to nominator's information of each user record the recommendation chain of site information.
Preferably, nominator's acquisition of information module 10 comprises nominator's information recording unit, is used for when the user accesses some websites information for the first time, judge to have or not the nominator, if do not have, then the nominator's information recording/ with this user is empty, if have, then record nominator's information; When this site information of user's subsequent access, do not change its original nominator's information.
Preferably, nominator's information recording unit comprises current nominator's information recording/subelement, is used for current nominator's the information recording/user record in its recommended.Recommendation chain determination module 20 comprises that first searches the unit, is used for receiving the user who recommends according to each user record from last and determines step by step the nominator forward, until the nominator is the user of active access websites information.
Preferably, nominator's information recording unit comprises recommends transmission of information record subelement, is used for the recommendation transmission of information before current nominator and the current nominator's information recording/user record in its recommended.Recommend chain determination module 20 to comprise that second searches the unit, recommend chain and nominator for obtaining the recommendation transmission of information that receives the user record of recommending from last.
Preferably, statistical module 30 comprises taxon, is used for obtaining the feedback information of recommending each user of chain, and the user that will have identical feedback is divided into a class; Or location information acquiring unit, be used for obtaining the positional information of recommending each user of chain, according to each user the feedback information of site information is added up site information in the degree that is accepted in each place.
With reference to Fig. 5, preferably, system also comprises effective nominator's determination module 50, is used for obtaining recommending each user of chain to the feedback information of site information, and determines effectively recommendation chain and effectively nominator according to field feedback.
Preferably, system also comprises the allocation rule determination module, is used for setting allocation rule, rewards distribution to all effective nominators.
Each embodiment in this instructions all adopts the mode of going forward one by one to describe, and what each embodiment stressed is and the difference of other embodiment that identical similar part is mutually referring to getting final product between each embodiment.For system embodiment because itself and embodiment of the method basic simlarity, so describe fairly simple, relevant part gets final product referring to the part explanation of embodiment of the method.
Above site information recommending data disposal route and the system that the application is provided is described in detail, used specific case herein the application's principle and embodiment are set forth, the explanation of above embodiment just is used for helping to understand the application's method and core concept thereof; Simultaneously, for one of ordinary skill in the art, the thought according to the application all will change in specific embodiments and applications, and in sum, this description should not be construed as the restriction to the application.
Claims (18)
1. a site information recommending data disposal route is characterized in that, may further comprise the steps:
Obtain the operation of nominator recommended website information, and in receiving the user record of recommending, record nominator's information;
Determine the recommendation chain of site information according to the nominator's information in the user record;
According to the user profile of recommending each user in the chain, the recommending data of site information is added up.
2. the method for claim 1 is characterized in that, the described nominator's information that records in receiving the user record of recommending comprises:
When the user accesses some websites information for the first time, judge to have or not the nominator, if do not have, then the nominator's information recording/ with this user is empty, if having, then records nominator's information;
When this site information of user's subsequent access, do not change its original nominator's information.
3. method as claimed in claim 2 is characterized in that, described record nominator information comprises:
With current nominator's information recording/in the user record of its recommended.
4. method as claimed in claim 3 is characterized in that, the recommendation chain of described definite site information comprises:
Choose a user, determine step by step the nominator forward, until the nominator is the user of active access websites information.
5. method as claimed in claim 2 is characterized in that, described record nominator information comprises:
Will be at the recommendation transmission of information before the current nominator and current nominator's information recording/in the user record in its recommended.
6. method as claimed in claim 5 is characterized in that, the recommendation chain of described definite site information comprises:
Choose a user, the recommendation transmission of information from this user's user record obtains the recommendation chain.
7. the method for claim 1 is characterized in that, the operation of the described nominator of obtaining recommended website information comprises:
Obtain the nominator and copy the corresponding operation that links of site information, nominator's information is added in the link, from described link, obtain this nominator's information; Or
Obtain the nominator and click the operation of corresponding button in the website, generate the recommendation message that includes nominator's information, from described recommendation message, obtain this nominator's information.
8. such as each described method of claim 1 to 7, it is characterized in that described user profile according to recommending each user in the chain is added up the recommending data of site information and to be comprised:
Obtain the feedback information of recommending each user in the chain, the user that will have identical feedback information is divided into a class; Or
Obtain the positional information of recommending each user in the chain, according to each user the feedback information of site information is added up site information in the degree that is accepted in each place.
9. method as claimed in claim 8 is characterized in that, the described feedback information of recommending each user in the chain that obtains, and the user that will have identical feedback is divided into a class and also comprises afterwards:
Obtain all types of user preference according to classification results;
Choose all types of user according to user preference and wish that the site information that obtains shows it.
10. the method for claim 1 is characterized in that, described method also comprises:
Obtain and recommend in the chain each user to the feedback information of site information;
Determine effectively to recommend chain and effective nominator according to field feedback.
11. a site information commending system is characterized in that, comprising:
Nominator's acquisition of information module for the operation of obtaining nominator recommended website information, and records nominator's information in receiving the user record of recommending;
Recommend the chain determination module, be used for determining according to nominator's information of user record the recommendation chain of site information;
Statistical module is used for according to the user profile of recommending each user of chain the recommending data of site information being added up.
12. system as claimed in claim 11 is characterized in that, described nominator's acquisition of information module comprises:
Nominator's information recording unit is used for when the user accesses some websites information for the first time, judges to have or not the nominator, if do not have, then the nominator's information recording/ with this user is empty, if having, then records nominator's information; When this site information of user's subsequent access, do not change its original nominator's information.
13. system as claimed in claim 12 is characterized in that, described nominator's information recording unit comprises:
Current nominator's information recording/subelement is used for current nominator's the information recording/user record in its recommended.
14. system as claimed in claim 13 is characterized in that, described recommendation chain determination module comprises:
First searches the unit, is used for receiving the user who recommends according to each user record from last and determines step by step the nominator forward, until the nominator is the user of active access websites information.
15. system as claimed in claim 12 is characterized in that, described nominator's information recording unit comprises:
Recommend the transmission of information record cell, be used for the recommendation transmission of information before current nominator and the current nominator's information recording/user record in its recommended.
16. system as claimed in claim 15 is characterized in that, described recommendation chain determination module comprises:
Second searches the unit, obtains for the recommendation transmission of information that receives the user record of recommending from last and recommends chain and nominator.
17. such as each described system of claim 11 to 16, it is characterized in that, described statistical module comprises:
Taxon is used for obtaining the feedback information of recommending each user of chain, and the user that will have identical feedback is divided into a class; Or
Location information acquiring unit is used for obtaining the positional information of recommending each user of chain, according to each user the feedback information of site information is added up site information in the degree that is accepted in each place.
18. system as claimed in claim 11 is characterized in that, described system also comprises:
Effectively nominator's determination module is used for obtaining each user of recommendation chain to the feedback information of site information, and determines effectively to recommend chain and effective nominator according to field feedback.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110247866.9A CN102955805B (en) | 2011-08-24 | 2011-08-24 | Recommendation data of website information processing method and system |
| HK13104559.0A HK1177525A1 (en) | 2011-08-24 | 2013-04-16 | Method and system for processing website information recommendation data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110247866.9A CN102955805B (en) | 2011-08-24 | 2011-08-24 | Recommendation data of website information processing method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102955805A true CN102955805A (en) | 2013-03-06 |
| CN102955805B CN102955805B (en) | 2016-06-29 |
Family
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
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| CN201110247866.9A Active CN102955805B (en) | 2011-08-24 | 2011-08-24 | Recommendation data of website information processing method and system |
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| CN (1) | CN102955805B (en) |
| HK (1) | HK1177525A1 (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105487861A (en) * | 2015-11-26 | 2016-04-13 | 珠海多玩信息技术有限公司 | Method and apparatus for acquiring component calling amount |
| CN106846132A (en) * | 2017-04-12 | 2017-06-13 | 杭州纳戒科技有限公司 | Merchandise news method for pushing, device and system |
| CN107111846A (en) * | 2015-01-13 | 2017-08-29 | 索尼公司 | Message processing device, information processing method and program |
| CN111556330A (en) * | 2020-04-30 | 2020-08-18 | 许周 | Electronic commerce information pushing method based on artificial intelligence and artificial intelligence cloud platform |
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| CN1608268A (en) * | 2001-12-28 | 2005-04-20 | 皇家飞利浦电子股份有限公司 | Method of enabling e-commerce |
| CN101103368A (en) * | 2004-11-30 | 2008-01-09 | 阿诺·马索尼 | Open system for dynamically generating a network of contacts |
| CN101464983A (en) * | 2007-12-18 | 2009-06-24 | 汤溪蔚 | Electronic commercial matters application method and system |
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| CN101944135A (en) * | 2010-10-22 | 2011-01-12 | 道有道(北京)科技有限公司 | Information processing system and method |
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| CN1608268A (en) * | 2001-12-28 | 2005-04-20 | 皇家飞利浦电子股份有限公司 | Method of enabling e-commerce |
| CN101103368A (en) * | 2004-11-30 | 2008-01-09 | 阿诺·马索尼 | Open system for dynamically generating a network of contacts |
| CN101464983A (en) * | 2007-12-18 | 2009-06-24 | 汤溪蔚 | Electronic commercial matters application method and system |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107111846A (en) * | 2015-01-13 | 2017-08-29 | 索尼公司 | Message processing device, information processing method and program |
| CN105487861A (en) * | 2015-11-26 | 2016-04-13 | 珠海多玩信息技术有限公司 | Method and apparatus for acquiring component calling amount |
| CN105487861B (en) * | 2015-11-26 | 2018-11-27 | 珠海多玩信息技术有限公司 | The method and device of securing component calling amount |
| CN106846132A (en) * | 2017-04-12 | 2017-06-13 | 杭州纳戒科技有限公司 | Merchandise news method for pushing, device and system |
| CN111556330A (en) * | 2020-04-30 | 2020-08-18 | 许周 | Electronic commerce information pushing method based on artificial intelligence and artificial intelligence cloud platform |
| CN111556330B (en) * | 2020-04-30 | 2021-01-05 | 赵勇奎 | Electronic commerce information pushing method based on artificial intelligence and artificial intelligence cloud platform |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102955805B (en) | 2016-06-29 |
| HK1177525A1 (en) | 2013-08-23 |
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