Case-reasoning-based personalized recommendation method for E-commerce website commodity

A technology for e-commerce websites and recommendation methods, which is applied in the field of e-commerce personalized recommendation and personalized recommendation of products on e-commerce websites, and can solve problems such as difficult and difficult to update personalized recommendation information in real time

Inactive Publication Date: 2015-08-19
XIANGNAN UNIV
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AI Technical Summary

Problems solved by technology

Conventional personalized recommendation technology learns user interests and behaviors by collecting and analyzing user information, and it is difficult to update in real time and proactively provide fine personalized recommendation information to users
At the same time, the system collects high-dimensional sparsity of user information and behaviors, and it is difficult to use these scarce information to provide accurate recommendations for other users. With the increase of users, the information becom

Method used

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  • Case-reasoning-based personalized recommendation method for E-commerce website commodity
  • Case-reasoning-based personalized recommendation method for E-commerce website commodity
  • Case-reasoning-based personalized recommendation method for E-commerce website commodity

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[0037] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments.

[0038] The personalized recommendation method of e-commerce website products based on case-based reasoning of the present invention, such as image 3 As shown, including the following steps:

[0039] Step S1: Construct a target problem with the characteristics and visit behavior of the current visiting user, and construct the original case with the characteristics of other users and their historical visit behavior and purchase records. The establishment methods include:

[0040] 101: Establish a case system of four tuples (U, A, V, F); where U = {u 1 , U 2 ,..., u n } Is the set of case entities, called the universe of discourse; case space A=C∪D, C is the conditional attribute set, D is the decision set; V=∨V a Is the collection of all attribute values, V a Is the range of attribute a; F is a function of U×A→V. The domain of discourse can be divided a...

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Abstract

The invention relates to a case-reasoning-based personalized recommendation method for an E-commerce website commodity. An objective problem is constructed according to a feature and an access behavior of a current access user and an original case is established according to features, historical access behaviors, and purchase records of other users; a fuzzy clustering way is used for carrying out clustering according to a target case feature, cases with high similarity levels of user features and interests and the like are classified into the same class and the class is identified, and a high-similarity-level case base is established; and a resolved case set most similar to the target user case is recommended by using a user case similarity retrieval and an improved fuzzy mean clustering algorithm and then is corrected and reused, and a dynamic case base is also updated. According to the invention, the system real-time performance is enhanced; and a problem that the previous recommendation system relies too much on commodity evaluation by users can be solved.

Description

technical field [0001] The invention belongs to the field of computer technology, and relates to e-commerce personalized recommendation technology, in particular to a case-based reasoning method for personalized recommendation of commodities on an e-commerce website. , Background technique [0002] In the "big data network environment", e-commerce companies are required to use big data processing systems to track consumers from unconscious website browsing to product purchases and post-purchase behaviors, and to make more real-time and more personalized solutions for the individual needs of different consumers. recommended. Conventional personalized recommendation technology learns user interests and behaviors by collecting and analyzing user information, and it is difficult to update in real time and actively provide fine personalized recommendation information to users. At the same time, the system collects high-dimensional sparsity of user information and behaviors, and...

Claims

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Application Information

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IPC IPC(8): G06Q30/02
Inventor 陈雪刚
Owner XIANGNAN UNIV
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