Product similarity based e-commerce recommendation system and method thereof

A technology of e-commerce and recommendation system, applied in the direction of digital data processing, special data processing applications, instruments, etc., can solve the problems of inability to realize accurate product recommendation, inability to meet the selection of personalized products, etc.

Inactive Publication Date: 2014-07-23
BEIJING LIANJIA ZHONGYING NETWORK TECH CO LTD
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0007] However, in the process of realizing the present invention, the inventors of the present invention have found that there are at least the following problems in the prior art: the common interest of the target user's neighbor users and the target user is not only for the interest of the product, but may

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  • Product similarity based e-commerce recommendation system and method thereof
  • Product similarity based e-commerce recommendation system and method thereof
  • Product similarity based e-commerce recommendation system and method thereof

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Embodiment Construction

[0054] In order to make the above objects, features and advantages of the present invention more comprehensible, the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0055] The e-commerce recommendation system based on product similarity provided by the present invention can be applied to various shopping websites. By analyzing the consumption preferences of users, it can recommend products to each user in a targeted manner. The recommendation system can not only help users from huge It can select products that really suit your needs from the product catalog, and can also return high-quality recommendation results according to the user's query requirements for specific products; the recommendation system recommends products similar to these products based on the products in the user's shopping basket. In addition, the recommendation system can also notify the product information of the recommended product by...

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Abstract

An embodiment of the invention discloses a product similarity based e-commerce recommendation system and a method thereof. The method of the product similarity based e-commerce recommendation system comprises analyzing e-commerce shopping website log information and performing filtration statics on the log; obtaining product popular information from a product database and performing weight customization; extracting corresponding recommendation information in combination with a user search log and the product popular information, establishing a similar product group through a collaborative filtering algorism which is based on the product similarity, transmitting data of similar products to a recommendation element redis; recommending a search engine with the http serving as a request protocol, supporting two recommendation functions according to different requirements (highly recommendation and browsing history recommendation), obtaining corresponding recommendation element set according to user parameters and expanding search query conditions to research; returning a recommendation result in Json data format. The method of the product similarity based e-commerce recommendation system has the advantages of improving the recommendation accuracy, achieving accurate recommendation of products and satisfying user requirements for selecting individualization products from mass products.

Description

technical field [0001] The invention relates to the field of computer applications, in particular to an e-commerce recommendation system and method based on product similarity. Background technique [0002] The traditional collaborative filtering recommendation system first searches for a group of users with similar interests to the target user, and these users with similar interests are often called neighbor users of the target user. The implementation process is to calculate the interest similarity between the target user and all other users through the cosine similarity algorithm. The specific algorithm is: [0003] T ( x , y ) = x • y | | x | | 2 ...

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Application Information

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IPC IPC(8): G06Q30/02G06F17/30
Inventor 王清霞张海旭杨威田列王振
Owner BEIJING LIANJIA ZHONGYING NETWORK TECH CO LTD
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