CN108346072A - Internet store commending system based on hybrid algorithm - Google Patents
Internet store commending system based on hybrid algorithm Download PDFInfo
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- CN108346072A CN108346072A CN201710049476.8A CN201710049476A CN108346072A CN 108346072 A CN108346072 A CN 108346072A CN 201710049476 A CN201710049476 A CN 201710049476A CN 108346072 A CN108346072 A CN 108346072A
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- store
- commodity
- interest
- commending system
- system based
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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—Recommending goods or services
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- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The present invention exists for traditional internet store commending system recommends the problems such as not comprehensive enough, passes through the store commending system of many algorithms hybrid technology fusion exploitation；It includes simple strategy that this system, which has used, the collaborative filtering technology of commodity similarity, the interest-degree algorithm of naive Bayesian recommends the commodity in store, allow user can merchandise news that is more clear and understanding this mall system, improve the income and service quality in store.
Description
Technical field
The invention belongs to Internet technical fields, relate to collaborative filtering technology and naive Bayesian.
Background technology
It is each in the electric business of internet, video, literature, social networks etc. at present with the continuous improvement of Internet technology
In class website or application, commending system all starts to have played the part of a more and more important role；Using the new of multiple technologies exploitation
Type store commending system can preferably service people.
Invention content
The master-plan of system
1. collaborative filtering technology：It is also browsed by user's commodity relation simple filtration, such as the user of the browsed commodity
It crosses;The user for buying this commodity also has purchased, and the user final 60% for browsing this commodity has purchased commodity A, 32 % and has purchased quotient
Product B, 8% has purchased commodity C;Commodity often bought together etc., while commodity are randomly choosed by multiclass mesh, it is pressed with classification
Commodity temperature ranking is used as interest-degree and is formed to target user by commodity similarity to predict that user does not buy the scorings of commodity
Push away
2. the interest-degree algorithm based on naive Bayesian：Data are bought according to user, interest probabilities are calculated by Bayesian formula
To calculate user to not buying the interest-degrees of commodity；The attribute of user is divided into natural quality and behavior property, and natural quality includes
User's gender, age, income, level of education etc., behavior property include browsing, buying, collecting, commenting on, being put into shopping cart etc.
Behavior；The attribute of commodity includes price, classification etc..
Claims (1)
1. the internet store commending system based on hybrid algorithm, it is characterised in that:It is general that interest is calculated by Bayesian formula
Rate calculates user to not buying the interest-degrees of commodity, while with simple strategy, the collaborative filtering based on commodity similarity
Technology, the interest-degree algorithm of naive Bayesian carry out structure and restrained high performance recommendation electronic emporium, and simple randomization recommends store
Merchandise news.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710049476.8A CN108346072A (en) | 2017-01-23 | 2017-01-23 | Internet store commending system based on hybrid algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710049476.8A CN108346072A (en) | 2017-01-23 | 2017-01-23 | Internet store commending system based on hybrid algorithm |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108346072A true CN108346072A (en) | 2018-07-31 |
Family
ID=62974597
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710049476.8A Withdrawn CN108346072A (en) | 2017-01-23 | 2017-01-23 | Internet store commending system based on hybrid algorithm |
Country Status (1)
| Country | Link |
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| CN (1) | CN108346072A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2720899C2 (en) * | 2018-09-14 | 2020-05-14 | Общество С Ограниченной Ответственностью "Яндекс" | Method and system for determining user-specific content proportions for recommendation |
| US10674215B2 (en) | 2018-09-14 | 2020-06-02 | Yandex Europe Ag | Method and system for determining a relevancy parameter for content item |
| US10706325B2 (en) | 2016-07-07 | 2020-07-07 | Yandex Europe Ag | Method and apparatus for selecting a network resource as a source of content for a recommendation system |
| USD890802S1 (en) | 2017-01-13 | 2020-07-21 | Yandex Europe Ag | Display screen with graphical user interface |
| US11086888B2 (en) | 2018-10-09 | 2021-08-10 | Yandex Europe Ag | Method and system for generating digital content recommendation |
| US11276076B2 (en) | 2018-09-14 | 2022-03-15 | Yandex Europe Ag | Method and system for generating a digital content recommendation |
| US11276079B2 (en) | 2019-09-09 | 2022-03-15 | Yandex Europe Ag | Method and system for meeting service level of content item promotion |
| US11288333B2 (en) | 2018-10-08 | 2022-03-29 | Yandex Europe Ag | Method and system for estimating user-item interaction data based on stored interaction data by using multiple models |
-
2017
- 2017-01-23 CN CN201710049476.8A patent/CN108346072A/en not_active Withdrawn
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10706325B2 (en) | 2016-07-07 | 2020-07-07 | Yandex Europe Ag | Method and apparatus for selecting a network resource as a source of content for a recommendation system |
| USD890802S1 (en) | 2017-01-13 | 2020-07-21 | Yandex Europe Ag | Display screen with graphical user interface |
| USD892847S1 (en) | 2017-01-13 | 2020-08-11 | Yandex Europe Ag | Display screen with graphical user interface |
| USD892846S1 (en) | 2017-01-13 | 2020-08-11 | Yandex Europe Ag | Display screen with graphical user interface |
| USD980246S1 (en) | 2017-01-13 | 2023-03-07 | Yandex Europe Ag | Display screen with graphical user interface |
| RU2720899C2 (en) * | 2018-09-14 | 2020-05-14 | Общество С Ограниченной Ответственностью "Яндекс" | Method and system for determining user-specific content proportions for recommendation |
| US10674215B2 (en) | 2018-09-14 | 2020-06-02 | Yandex Europe Ag | Method and system for determining a relevancy parameter for content item |
| US11263217B2 (en) | 2018-09-14 | 2022-03-01 | Yandex Europe Ag | Method of and system for determining user-specific proportions of content for recommendation |
| US11276076B2 (en) | 2018-09-14 | 2022-03-15 | Yandex Europe Ag | Method and system for generating a digital content recommendation |
| US11288333B2 (en) | 2018-10-08 | 2022-03-29 | Yandex Europe Ag | Method and system for estimating user-item interaction data based on stored interaction data by using multiple models |
| US11086888B2 (en) | 2018-10-09 | 2021-08-10 | Yandex Europe Ag | Method and system for generating digital content recommendation |
| US11276079B2 (en) | 2019-09-09 | 2022-03-15 | Yandex Europe Ag | Method and system for meeting service level of content item promotion |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20180731 |
|
| WW01 | Invention patent application withdrawn after publication |