E-commerce recommendation method of tracking user interest changes

A technology of e-commerce and recommendation method, which is applied in the field of e-commerce recommendation to track changes in user interests, and can solve problems such as the migration of user interest time that cannot be reflected in time.

Active Publication Date: 2014-03-05
ZHEJIANG UNIV
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Problems solved by technology

However, the classic collaborative filtering algorithm cannot timely reflect the migration of user interests over time. If the timel

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  • E-commerce recommendation method of tracking user interest changes
  • E-commerce recommendation method of tracking user interest changes

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[0034] With reference to accompanying drawing, further illustrate the present invention:

[0035] 1. After obtaining the user's historical data, perform the following operations:

[0036] 1) Aiming at the problem of sparse scoring matrix in the e-commerce recommendation system, comprehensively consider browsing behaviors such as user page stay time and mouse clicks, and obtain implicit scores, and then combine explicit scores to construct a comprehensive "user-product" that reflects user preferences scoring matrix;

[0037] 2) According to the rating records of users in the latest time period, combined with the existing product category information, the similarity of product category information between users is obtained;

[0038] 3) Calculate the rating similarity between users based on all rating records of users;

[0039] 4) Comprehensively consider the product category information similarity and rating similarity between users, and use a time-weighted collaborative filte...

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Abstract

An e-commerce recommendation method of tracking user interest changes is provided. Based on historical data of a user, the following operations are carried out sequentially: first, in view of a problem that a rating matrix is sparse in an e-commerce recommendation system, a user page retention time and other implicit feedbacks are used to obtain an implicit rating, an explicit rating is also use to construct a "user - commodity" comprehensive rating matrix which reflects a user preference; second, according to a rating record of the user in a recent period of time, an existing commodity category information is used to obtain a commodity category information similarity between users; and finally, a rating similarity and a commodity category information similarity between the users are comprehensively considered, and a collaborative filtering algorithm based on a time weight is used to recommend a most interesting commodity to the user. The advantages of the invention are that: the dynamic changes in the user interest are taken into the full consideration; and the commodity category information and the implicit feedback of the user are effectively used to recommend the commodity which is more in line with the current demand of the user.

Description

technical field [0001] The invention relates to the technical field of e-commerce recommendation systems, in particular to an e-commerce recommendation method for tracking user interest changes. Background technique [0002] Personalized recommendation technology mainly analyzes the behavior of different users, guesses user interests, and actively recommends resources to users, thereby alleviating the contradiction between the Internet information explosion and users' rapid acquisition of information, and also making up for the weak ability of general search engines to provide personalized feedback results. shortcoming. At present, recommendation technology is widely used in practical systems such as e-commerce, scientific literature retrieval, online music websites and digital libraries. [0003] In recent years, the emergence of e-commerce has brought about a revolutionary change in commodity circulation. First, the range of choices available to consumers has been greatly...

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Application Information

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IPC IPC(8): G06Q30/02
Inventor 卜佳俊王学庆李平陈纯孙仲浩
Owner ZHEJIANG UNIV
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