Socialized filtering method on basis of preference model

Abstract

The invention discloses a socialized filtering method on the basis of a preference model and mainly solves the problems of a great amount of targeted users, a complex social relationship and low accuracy of a filtering method in the prior art. The invention adopts the implementation scheme that the socialized filtering method on the basis of the preference model comprises the following steps of: calculating an influence factor of group members on a group by analyzing a socialization relationship among the group members; calculating an influence factor of preference objects of the group members to the group by analyzing the distribution of the preference objects of the group members in the group; integrating the two influence factors and carrying out character representation on the preference model of the group together to obtain a weighted influence vector of the group; and then calculating a filtration coefficient and judging the recommended condition to filter the common and like preference of the group, so that the accuracy and the efficiency of the socialized filtering method are improved. The socialized filtering method has the advantage of analysis on the preference model ofthe group. The recommendation of objects in different fields can be realized on the Internet only by modifying and acquiring keyword vectors in the fields.

Description

technical field [0001] The invention belongs to the technical field of information processing, and relates to collaborative filtering, in particular to a social filtering method, which can be used for information interaction and sharing in a network. Background technique [0002] With the development of the Internet, the network has become a platform for information sharing, on which users can interact and share information, so information sharing and interactive processing is an urgent problem to be solved. How to let people find the information they need in massive amounts of data and realize information sharing and interaction among users requires the use of collaborative filtering technology. This method does not depend on the attribute information of the user and the content information of the item, but only by analyzing a large amount of user behavior information on the item, find out a specific behavior pattern, and predict the user's preference accordingly. The so-c...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to address the deficiencies of the existing methods, to propose a social filtering method based on the preference model, and to establish group preference characteristics according to the relationship between users, so as to solve the problem that there are many users and the similarity of user preferences is relatively low In the case of , the accuracy of the user preference filtering method is improved by calculating the weighted influence vector of the group preference characteristics

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