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Collaborative filtering recommending method based on characteristics and credibility of users

A collaborative filtering recommendation and user feature technology, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve the problem of not considering the trust degree of different users, and achieve the effect of improving the accuracy of recommendation

Inactive Publication Date: 2014-04-30
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, the traditional collaborative filtering recommendation algorithm does not consider the degree of trust between different users.

Method used

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  • Collaborative filtering recommending method based on characteristics and credibility of users
  • Collaborative filtering recommending method based on characteristics and credibility of users
  • Collaborative filtering recommending method based on characteristics and credibility of users

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Embodiment Construction

[0029] see figure 1 , the method of the present invention respectively calculates the similarity between users according to the user's historical rating and characteristics of the project; selects an appropriate weight to combine the two similarities to obtain the final similarity between users; according to KNN (k Nearest Neighbors, K nearest method) method to calculate the user's nearest neighbor; the number of user's historical ratings is used as the trust degree, and the recommendation result is calculated by using the user's nearest neighbor matrix and the prediction formula adding the trust degree. The implementation steps are as follows:

[0030] Step 1, using the Pearson correlation coefficient and the Euclidean distance formula to construct a similarity matrix SimUser1(x,y) based on user ratings and user characteristics, and SimUser2(x,y) are as follows:

[0031] SimUser 1 ( x , y ...

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Abstract

The invention discloses a collaborative filtering recommending method based on the characteristics and credibility of users. The collaborative filtering recommending method based on the characteristics and credibility of the users comprises the following steps: respectively computing similarity between users according to the historical evaluating scores of users to a project and characteristics of the users; selecting proper weight to combine two kinds of similarity to obtain the finial similarity among the users; computing the nearest neighbor of the user according to KNN (K Nearest Neighbors) method; using the quantity of historical evaluating scores of the users as the credibility, and computing a recommending result by using the nearest neighbor matrix of the user and a predictor formula added with the credibility.

Description

technical field [0001] The present invention relates to a collaborative filtering recommendation method based on characteristic users and their trust degree, which introduces user characteristics and user trust degree on the basis of collaborative filtering, so as to alleviate the cold start problem and data sparsity problem of traditional collaborative filtering recommendation algorithm, and further Improving recommendation accuracy belongs to the field of personalized recommendation technology research. Background technique [0002] With the rapid development of the Internet and the massive growth of Internet information, the problem brought about is that it is difficult for users to find the information they need in a timely and accurate manner. Users need solutions that can organize and coordinate information according to their own characteristics, and personalized recommendation technology has emerged as the times require. [0003] At present, in the personalized recomm...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 王晓军冯旻远
Owner NANJING UNIV OF POSTS & TELECOMM
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