CN104182892A - Network shopping system based on recommendation - Google Patents
Network shopping system based on recommendation Download PDFInfo
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- CN104182892A CN104182892A CN201310193623.0A CN201310193623A CN104182892A CN 104182892 A CN104182892 A CN 104182892A CN 201310193623 A CN201310193623 A CN 201310193623A CN 104182892 A CN104182892 A CN 104182892A
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Abstract
The invention discloses a network shopping system based on recommendation, and thus users are given corresponding most-powerful shopping recommendations. The technical scheme is that the system comprises a network shopping module, a user goods sharing module, a vote summarizing module of recommended goods and a user recommendation authority calculation module, wherein the network shopping module is used for users to purchase goods on the network; the user goods sharing module is used for recommending the goods, each goods recommendation information comprising goods name, recommendation degree, sharing time and goods link; the vote summarizing module of the recommended goods is used for the other users to vote for the recommendation degree of some goods to show degree of recognition of the goods recommendation, and summarizing the vote results systematically; and the user recommendation authority calculation module is used for calculating the authority degree of the goods recommendation according to the vote result summarizing of some goods carried out by other users, so that the other users can refer to the authority degree before buying the goods.
Description
Technical field
The present invention relates to a kind of networked shopping system, relate in particular to the system of carrying out shopping at network based on user's commercial product recommending.
Background technology
In shopping, except seeing the brief introduction of commodity itself, people are more ready to look at the people that the bought evaluation for these commodity.Because brief introduction can be packed, sometimes there is certain not objectivity; And brief introduction has manufacturer or dealer to provide, people often can only obtain more positive information, and are not apprised of negative information.
Relatively acceptable scheme is, checks other people evaluation for these commodity, because for the user who there is no interests association, the evaluation that they have done has more objectivity.The comment that user makes also more comprehensively, can be covered part that do not mention or that cover in the information that businessman provides; And user comment has more practicality, what they made is all often the evaluation for the function of commodity own, more altisonant words in difference and businessman's brief introduction.
When but the recommendation at us based on user is chosen, we also can meet some problems.If while having a lot of users to make a lot of recommendation for commodity, but being limited to everyone the accumulation degree varies of experience causes, the suggestion that they provide is some difference perhaps, should now we the most authoritative suggestion of How to choose? if while only having little people to make recommendation for commodity, is how we believe known that whether this user's recommendation credible? a lot of time, the commodity that personnel's fake user of having interests relations is oneself are promoted, and how about do we accomplish not hoodwinked by them?
Summary of the invention
The object of the invention is to address the above problem, a kind of networked shopping system based on recommending is provided, recommend for user provides the most authoritative shopping accordingly.
Technical scheme of the present invention is: the present invention has disclosed a kind of networked shopping system based on recommending, and comprises that ballot statistical module and user that shopping at network module, user share merchandise module, recommended commodity recommend authoritative computing module, wherein:
Shopping at network module is bought commodity for user on network;
User shares merchandise module, and user recommends commodity, and the information of each commercial product recommending comprises trade name, recommendation degree, the time of sharing and commodity link;
The ballot statistical module of recommended commodity, other users vote to represent self degree of recognition to this commercial product recommending to a certain commercial product recommending, system is added up voting results;
User recommends authoritative computing module, according to other users, the voting results of a certain commercial product recommending is added up, and calculates the technorati authority of this commercial product recommending, for other users reference before buying commodity.
According to an embodiment of the networked shopping system based on recommending of the present invention, the recommendation information of commodity also comprises: commodity are experienced or commodity brief introduction, commodity picture and commodity relative merits.
According to an embodiment of the networked shopping system based on recommending of the present invention, the ballot statistical module of recommended commodity comprises:
Page browsing amount statistic unit, records the pageview of other users for this commercial product recommending;
Link clicks amount statistic unit, records other users and is browsing the click volume to its commodity link after this commercial product recommending;
Commodity trading volume statistic unit, records commodity link that other users provide according to this commercial product recommending and produces the trading volume of true commodity trading.
According to an embodiment of the networked shopping system based on recommending of the present invention, the principle that user recommends authoritative computing module to calculate the technorati authority of commercial product recommending is: each user is different for the technorati authority of commodity, user's technorati authority is to be determined by the degree of other customer's approvals by the commodity of its recommendation, technorati authority by the commercial product recommending of the higher customer's approval of technorati authority is higher, the number of candidates that user recommends same commodity and the value of its recommendation are inversely proportional to, the different candidates of user to same commodity recommendation degree may there are differences, same user changes along with the variation of time the recommendation of same commodity.
According to an embodiment of the networked shopping system based on recommending of the present invention, user recommends authoritative computing module to comprise:
User's technorati authority computing unit, the user that definition has N user gathers U, set up N N unit linear function: A{Ui}=A{R1}* σ 1+A{R2}* σ 2+...+A{Rn}* σ n, wherein Ui ∈ U, Ui is Sr{R1 for the set of the recommendation of commodity, R2...Rn}, for Ri ∈ Sr, there is user's subclass Uc{Ui1, Ui2...Uim} has carried out buying behavior by this link, note user's technorati authority is A, the purchase number of times that note Ui carries out altogether on commodity is TC, be Ti recommending the purchase number of times carrying out on Ri, the technorati authority of recommending Ri ∈ Sr is A{Ri}=Ui1*Ti1/TC1+Ui2*Ti2/TC2+...+Uim*Tim/TCm, σ i is the weak factor of the time of technorati authority, solution of equations is the value of user's technorati authority, wherein N is natural number,
Commercial product recommending technorati authority computing unit, calculate the technorati authority of each recommendation: A{Rn}=A{Ui}*Drn/SUMd* σ n, wherein user Ui for the recommendation degree of all recommendations and be SUMd=Dr1* σ 1+Dr2* σ 2+...+Drn* σ n, the recommendation degree of Ri ∈ Sr is Dri.
The present invention contrasts prior art following beneficial effect: the solution of the present invention is the commercial product recommending based on user, and other users according to these recommend produce browse, click, buying behavior carrys out the authoritative degree of overall calculating user for commercial product recommending, and then calculate the authoritative degree of the commercial product recommending that user provides, thereby recommend for user provides the most authoritative shopping accordingly, can the recommendation of guides user based on objectively the most authoritative buy commodity.
Brief description of the drawings
Fig. 1 shows the schematic diagram of the preferred embodiment of the networked shopping system based on recommending of the present invention.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described.
Fig. 1 shows the principle of the preferred embodiment of the networked shopping system based on recommending of the present invention.Refer to Fig. 1, the networked shopping system of the present embodiment comprises: ballot statistical module 3 and user that shopping at network module 1, user share merchandise module 2, recommended commodity recommend authoritative computing module 4.
Shopping at network module 1 is bought commodity for user on network.
User shares in merchandise module 2, and user recommends commodity, and the information of each commercial product recommending comprises trade name, recommendation degree, the time of sharing and commodity link.Preferably, the recommendation information of commodity also comprises: commodity are experienced or commodity brief introduction, commodity picture and commodity relative merits.For user, for same commodity, they may provide one or more recommendation.And As time goes on, their recommendation also changes occurring; For commodity, same commodity, may be provided different recommendations by one or more user.
In the ballot statistical module 3 of recommended commodity, other users vote to represent self degree of recognition to this commercial product recommending to a certain commercial product recommending, and system is added up voting results.
User, for a kind of technorati authority of commodity, mainly comes from the degree of recognition that other users recommend him.For user's recommendation, shopper may browse recommended commodity out; If interested for recommended content, they may click the link providing; If also comparative maturity of other condition, user may remove to buy the commodity of recommending according to this link.
Therefore, the ballot statistical module 3 of recommended commodity comprises: page browsing amount statistic unit 31, link clicks amount statistic unit 32 and commodity trading volume statistic unit 33.
Wherein page browsing amount statistic unit 31 records the pageview of other users for this commercial product recommending.Link clicks amount statistic unit 32 records other users and is browsing the click volume to its commodity link after this commercial product recommending.Commodity trading volume statistic unit 33 records commodity link that other users provide according to this commercial product recommending and produces the trading volume of true commodity trading.
User recommends authoritative computing module 4 according to other users, the voting results of a certain commercial product recommending to be added up, and calculates the technorati authority of this commercial product recommending, for other users reference before buying commodity.
The principle that user recommends authoritative computing module 4 to calculate the technorati authority of commercial product recommending is: each user is different for the technorati authority of commodity, user's technorati authority is to be determined by the degree of other customer's approvals by the commodity of its recommendation, technorati authority by the commercial product recommending of the higher customer's approval of technorati authority is higher, number of candidates and the value of its recommendation that user recommends same commodity is inversely proportional to, and (extreme case is allly all to recommend, can think that what does not all recommend), the different candidates of user to same commodity recommendation degree may there are differences, same user changes along with the variation of time the recommendation of same commodity.
User recommends computing module 4 to comprise user's technorati authority computing unit 41 and commercial product recommending technorati authority computing unit 42.In user's technorati authority computing unit 41, suppose user Ui, for commodity G, having provided the set of recommending is Sr{R1, R2...Rn}.For Ri ∈ Sr, there is user's subclass Uc{Ui1, Ui2...Uim} has carried out buying behavior by this link.
Note user's technorati authority is A, and the number of times that note Ui has carried out altogether buying on commodity G is TC, is Ti recommending the purchase number of times carrying out on Ri, and the technorati authority of recommending Ri ∈ Sr is A{Ri}=Ui1*Ti1/TC1+Ui2*Ti2/TC2+...+Uim*Tim/TCm
The technorati authority of user Ui is A{Ui}=A{R1}+A{R2}+...+A{Rn}
As time goes on the enjoing ability of considering user can change, and introduces the concept of the weak factor in the present embodiment, the weak factor of time that definition σ is technorati authority.
Above-mentioned formula is deformed into A{Ui}=A{R1}* σ 1+A{R2}* σ 2+...+A{Rn}* σ n
In like manner, also process by above-mentioned processing procedure for other users in set U (total N user), through a series of abbreviation, obtained N N unit linear function, this solution of equations is the value of user's technorati authority, can ask numerical solution by sparse matrix.
In commercial product recommending technorati authority computing unit 42, the value of the technorati authority by user solves the technorati authority of each recommendation.Had temporal delay due to what recommend by sure degree, it is considered herein that recommended commodity only have on referrer's recommendation degree to distinguish.
The recommendation degree that note is recommended is D, and the recommendation degree of Ri ∈ Sr is Dri.
User Ui for the recommendation degree of all recommendations and be calculated as for the technorati authority of each recommendation for SUMd=Dr1* σ 1+Dr2* σ 2+...+Drn* σ n:
A{R1}＝A{Ui}*Dr1/SUMd*σ1
A{R2}＝A{Ui}*Dr2/SUMd*σ2
…
A{Rn}＝A{Ui}*Drn/SUMd*σn
Above-described embodiment is available to those of ordinary skill in the art and realizes and use of the present invention; those of ordinary skill in the art can be without departing from the present invention in the case of the inventive idea; above-described embodiment is made to various modifications or variation; thereby protection scope of the present invention do not limit by above-described embodiment, and it should be the maximum magnitude that meets the inventive features that claims mention.
Claims (5)
1. the networked shopping system based on recommending, comprises that ballot statistical module and user that shopping at network module, user share merchandise module, recommended commodity recommend authoritative computing module, wherein:
Shopping at network module is bought commodity for user on network;
User shares merchandise module, and user recommends commodity, and the information of each commercial product recommending comprises trade name, recommendation degree, the time of sharing and commodity link;
The ballot statistical module of recommended commodity, other users vote to represent self degree of recognition to this commercial product recommending to a certain commercial product recommending, system is added up voting results;
User recommends authoritative computing module, according to other users, the voting results of a certain commercial product recommending is added up, and calculates the technorati authority of this commercial product recommending, for other users reference before buying commodity.
2. the networked shopping system based on recommending according to claim 1, is characterized in that, the recommendation information of commodity also comprises: commodity are experienced or commodity brief introduction, commodity picture and commodity relative merits.
3. the networked shopping system based on recommending according to claim 1, is characterized in that, the ballot statistical module of recommended commodity comprises:
Page browsing amount statistic unit, records the pageview of other users for this commercial product recommending;
Link clicks amount statistic unit, records other users and is browsing the click volume to its commodity link after this commercial product recommending;
Commodity trading volume statistic unit, records commodity link that other users provide according to this commercial product recommending and produces the trading volume of true commodity trading.
4. the networked shopping system based on recommending according to claim 3, it is characterized in that, the principle that user recommends authoritative computing module to calculate the technorati authority of commercial product recommending is: each user is different for the technorati authority of commodity, user's technorati authority is to be determined by the degree of other customer's approvals by the commodity of its recommendation, technorati authority by the commercial product recommending of the higher customer's approval of technorati authority is higher, the number of candidates that user recommends same commodity and the value of its recommendation are inversely proportional to, the different candidates of user to same commodity recommendation degree may there are differences, same user changes along with the variation of time the recommendation of same commodity.
5. the networked shopping system based on recommending according to claim 3, is characterized in that, user recommends authoritative computing module to comprise:
User's technorati authority computing unit, the user that definition has N user gathers U, set up N N unit linear function: A{Ui}=A{R1}* σ 1+A{R2}* σ 2+...+A{Rn}* σ n, wherein Ui ∈ U, Ui is Sr{R1 for the set of the recommendation of commodity, R2...Rn}, for Ri ∈ Sr, there is user's subclass Uc{Ui1, Ui2...Uim} has carried out buying behavior by this link, note user's technorati authority is A, the purchase number of times that note Ui carries out altogether on commodity is TC, be Ti recommending the purchase number of times carrying out on Ri, the technorati authority of recommending Ri ∈ Sr is A{Ri}=Ui1*Ti1/TC1+Ui2*Ti2/TC2+...+Uim*Tim/TCm, σ i is the weak factor of the time of technorati authority, solution of equations is the value of user's technorati authority, wherein N is natural number,
Commercial product recommending technorati authority computing unit, calculate the technorati authority of each recommendation: A{Rn}=A{Ui}*Drn/SUMd* σ n, wherein user Ui for the recommendation degree of all recommendations and be SUMd=Dr1* σ 1+Dr2* σ 2+...+Drn* σ n, the recommendation degree of Ri ∈ Sr is Dri.
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| CN201310193623.0A CN104182892A (en) | 2013-05-22 | 2013-05-22 | Network shopping system based on recommendation |
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| CN201310193623.0A CN104182892A (en) | 2013-05-22 | 2013-05-22 | Network shopping system based on recommendation |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104835058A (en) * | 2015-04-15 | 2015-08-12 | 华为技术有限公司 | Method and device for sharing commodity link |
| CN104951960A (en) * | 2015-05-21 | 2015-09-30 | 腾讯科技（北京）有限公司 | Target information based interaction method and target information based interaction device |
| CN105260927A (en) * | 2015-11-09 | 2016-01-20 | 无锡阅威信息科技有限公司 | Virtual shopping cart system with function of credit exchange on different platforms |
| CN105303409A (en) * | 2015-11-09 | 2016-02-03 | 无锡阅威信息科技有限公司 | PC or PDA version online shopping system |
| CN106447457A (en) * | 2016-10-13 | 2017-02-22 | 乐视控股（北京）有限公司 | Information processing method and apparatus, server, and electronic device |
| CN108304541A (en) * | 2018-01-31 | 2018-07-20 | 刘世洪 | The structure system and method for user preferences modeling UIM based on technique transfers platform |
| CN110310120A (en) * | 2019-07-08 | 2019-10-08 | 湖南共睹互联网科技有限责任公司 | Guarantee method of commerce, device and the storage medium participated in based on eye-witness |
| CN112819502A (en) * | 2015-10-09 | 2021-05-18 | 徐蔚 | Information dissemination method based on commodity circulation, server and mobile terminal |
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2013
- 2013-05-22 CN CN201310193623.0A patent/CN104182892A/en active Pending
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104835058A (en) * | 2015-04-15 | 2015-08-12 | 华为技术有限公司 | Method and device for sharing commodity link |
| CN104835058B (en) * | 2015-04-15 | 2018-07-31 | 华为技术有限公司 | A kind of sharing method and device of goods links |
| CN104951960A (en) * | 2015-05-21 | 2015-09-30 | 腾讯科技（北京）有限公司 | Target information based interaction method and target information based interaction device |
| CN104951960B (en) * | 2015-05-21 | 2019-04-16 | 腾讯科技（北京）有限公司 | Exchange method and device based on object message |
| CN112819502A (en) * | 2015-10-09 | 2021-05-18 | 徐蔚 | Information dissemination method based on commodity circulation, server and mobile terminal |
| CN105260927A (en) * | 2015-11-09 | 2016-01-20 | 无锡阅威信息科技有限公司 | Virtual shopping cart system with function of credit exchange on different platforms |
| CN105303409A (en) * | 2015-11-09 | 2016-02-03 | 无锡阅威信息科技有限公司 | PC or PDA version online shopping system |
| CN106447457A (en) * | 2016-10-13 | 2017-02-22 | 乐视控股（北京）有限公司 | Information processing method and apparatus, server, and electronic device |
| CN108304541A (en) * | 2018-01-31 | 2018-07-20 | 刘世洪 | The structure system and method for user preferences modeling UIM based on technique transfers platform |
| CN110310120A (en) * | 2019-07-08 | 2019-10-08 | 湖南共睹互联网科技有限责任公司 | Guarantee method of commerce, device and the storage medium participated in based on eye-witness |
| CN110310120B (en) * | 2019-07-08 | 2022-02-11 | 湖南共睹互联网科技有限责任公司 | Guarantee transaction method, device and storage medium based on witness participation |
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