Method for improving social recommendation efficiency based on user personality

A user and personality technology, applied in the field of recommendation system, can solve the problems of ignoring the referral willingness of friends and referees and low efficiency, so as to achieve the effect of effective recommendation, improved efficiency and favorable acceptance

Inactive Publication Date: 2013-09-18
EAST CHINA NORMAL UNIV
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Problems solved by technology

However, the efficiency of this friend recommendation method is still very low at present. The main reason is that the recommendation willingness of the friends themselves (hereinafter collectively referred to as the referrer) is ignored, that is, the selected referrer is not very willing to pass the relevant products to the social network, resulting in referral The efficiency of the method is much lower than the method directly recommended by the system

Method used

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  • Method for improving social recommendation efficiency based on user personality
  • Method for improving social recommendation efficiency based on user personality

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Experimental program
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Embodiment

[0044] The present invention is better understood through the following movie-recommended examples.

[0045] Assuming that we want to use social recommendation (that is, through friends) to recommend movies to a target user, the specific steps are as follows:

[0046] (1) Through the user-based collaborative filtering algorithm, select k (here, 2) movies to be recommended from the movie set that the target user has not seen, which are "Lost in Thailand" and "Frankenstein";

[0047] (2) Choose one of the movies (such as "Lost in Thailand") as the movie to be recommended;

[0048] (3) Obtain the set of all friends of the target user in the system F={f 1, f 2, f 3};

[0049] (4) Since the number of friends |F|>0, go to step (5);

[0050] (5) Obtain the score s_p of each friend in the personality dimension "Pleasantness" and the rating s_r (actual or predicted) of the movie's preference, see figure 2 ;

[0051] (6) by formula Calculate the comprehensive recommendation...

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Abstract

The invention discloses a method for improving the social recommendation efficiency based on user personality. The method comprises the steps as follows: a, determining k commodities to be recommended to a target user; b, for each commodity m to be recommended, calculating the comprehensive recommendation scores of the good friends of the target user based on personalities and commodity preferences respectively, and selecting the friend with the highest score as a corresponding recommender of the commodity m; and c, notifying each recommender to recommend the corresponding commodity to the target user. According to the method, the proper recommender is selected according to the user personality features and the commodity preferences, so that the recommendation efficiency is improved; and the method has the advantages as follows: the loss in a recommendation transfer process can be further reduced, the circulation of the commodities in a social network can be further promoted, and the social recommendation efficiency can be further improved.

Description

technical field [0001] The present invention relates to the field of recommendation system research that improves the social recommendation method to improve its efficiency. Specifically, among the friends of the target user, the person who is more willing to recommend products to others in terms of psychological characteristics (referring to personality) is found as the referrer , to improve the possibility of products reaching target users, thereby improving the efficiency of social referrals. Background technique [0002] In the research on social recommendation, researchers often focus on how to use the user's social relationship to provide explanations for the recommendation results (for example, if product m appears in the system recommendation list, it will be additionally stated that m is liked by some friends), so as to increase User trustworthiness. At this stage, some researchers have begun to study the difference between the direct recommendation of the system a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q30/02
Inventor 贺樑陈琴徐晓枫罗念潘云黄保荃
Owner EAST CHINA NORMAL UNIV
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