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
View PDF2 Cites 35 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • 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

Examples

Experimental program
Comparison scheme
Effect test

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 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap