Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Mixed recommendation method based on excavation of user behavior compositing factor

A recommendation method and hybrid recommendation technology, which is applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as the decline in the quality of user interest models

Active Publication Date: 2015-07-29
SOUTHEAST UNIV
View PDF4 Cites 22 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The reduction of feature information may lead to a decrease in the quality of the user interest model

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
  • Mixed recommendation method based on excavation of user behavior compositing factor
  • Mixed recommendation method based on excavation of user behavior compositing factor
  • Mixed recommendation method based on excavation of user behavior compositing factor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0070] The present invention will be further described below in conjunction with the accompanying drawings.

[0071] A hybrid recommendation method based on mining compound factors of user behavior, including three parts: a recommendation method for user personality factors, a recommendation method for user commonality factors, and adaptive hybrid calculation. Suppose there are a total of U users and M items and N item attributes, user u has given evaluations to Q items among them, forming an item set Q(u); the specific implementation process is as follows:

[0072] (1) Recommendation method for user personality factors:

[0073] The item-based collaborative filtering algorithm recommends items similar to items previously evaluated by the user, specifically: for item i, select K items most similar to item i from the item set Q(u) corresponding to user u to form a set S(i, K), the similarity ω between item k and item i in the set S(i, K) ik is the weight to predict the rating...

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 mixed recommendation method based on excavation of a user behavior compositing factor. From the point of view of user behavior influencing factors (personalized factors and common factors), in allusion to each influencing factor, a personalized recommendation algorithm is provided so as to fully extract influence of the influencing factor on user behavior; finally, according to historical data of users, recommendation results reflecting the two kinds of influencing factors are dynamically mixed, and personalized recommendation services are provided for different users.

Description

technical field [0001] The invention relates to a hybrid recommendation method based on mining compound factors of user behavior. Background technique [0002] Acronyms and key term definitions [0003] CF collaborative filtering Collaborative filtering [0004] CBF content-based filtering content-based filtering [0005] ItemCF Item-based collaborative filtering [0006] UserCF User-based collaborative filtering User-based collaborative filtering [0007] SP-ItemCF Special Factor Item-based filtering Priority personality factor improved collaborative filtering algorithm based on items [0008] COM-UserCF Common Factor User-based filtering The improvement of the priority common factor is based on the user-based collaborative filtering algorithm [0009] The recommendation system is an information filtering system to solve the problem of information overload. The recommendation system technology has a long history of development, during which a large number of recommend...

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
IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 徐平平刘博宇
Owner SOUTHEAST UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com