Collaborative filtering recommendation method based on user preferences

A collaborative filtering recommendation and user technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of calculating user similarity deviation, low user scoring, affecting recommendation quality, etc., to achieve accurate similarity, reduce Chance, the effect of improving recommendation quality

Inactive Publication Date: 2017-07-28
HEFEI UNIV OF TECH
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AI Technical Summary

Problems solved by technology

However, users have preference behaviors when scoring, and there are situations where users score low or high, and users with similar interests als

Method used

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  • Collaborative filtering recommendation method based on user preferences
  • Collaborative filtering recommendation method based on user preferences
  • Collaborative filtering recommendation method based on user preferences

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Embodiment Construction

[0072] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0073] refer to figure 1 As shown, the collaborative filtering recommendation method based on user preference in the present invention includes the following steps:

[0074] Step 1: Input the user-item rating matrix, take the average rating of all user ratings, set it as the threshold p, and divide users into users who prefer high ratings and users who prefer low ratings according to the threshold p;

[0075] Step 2: Use the NHSM similarity measurement method to calculate the similarity between any two users, and obtain the similarity matrix sim between users;

[0076] Step 3: Set the target user U a , the user ...

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Abstract

The invention discloses a collaborative filtering recommendation method based on user preferences. The method includes the following steps that according to a threshold value p, users are divided into with high-score preference users and low-score preference users; an NHSM similarity measuring method is adopted to calculate the similarity between any two users, and a similarity matrix among the users is obtained; target users Ua are set, a same-preference user group of the target user Ua is s, a different-preference user group of the target user Ua is d, the similarity between the target users Ua and other users Ub is calculated; a new similarity matrix Newsim among the users is calculated; scores which the target users Ua give for un-scored items by the target users Ua are predicted. Compared with the prior art, the collaborative filtering recommendation method based on the user preferences has the following advantages that a collaborative filtering recommendation model is constructed on the basis of the user preferences and the contingency of predicted results is reduced. Test results show that compared with other recommendation methods, through the collaborative filtering recommendation method based on the user preferences, the similarity among users can be more accurately measured, and the recommendation quality is improved.

Description

technical field [0001] The invention relates to the field of Internet personalized recommendation, in particular to a collaborative filtering recommendation method based on user preference. Background technique [0002] The rapid development of Internet technology has increased the capacity of web information, how to provide users with valuable information has become a problem that e-commerce must face. The recommendation system understands and grasps the user's preferences by learning the user's behavior, so that it can recommend more targeted content to the user that they may be interested in. Collaborative filtering is a popular technology in recommender systems, which can effectively solve the problem of information overload, help users quickly find valuable information, and filter useless information. The basic idea is: according to the user's purchase records, rating records, browsing records and annotations, etc., recommend the information needed by the user or predi...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 胡学钢杨恒宇林耀进
Owner HEFEI UNIV OF TECH
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