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

Information recommending method and device

A technology of information recommendation and historical information, which is applied in the field of information recommendation methods and devices, can solve the problems of data sparseness and low accuracy of recommendation systems, and achieve the effects of reducing data volume, improving efficiency and accuracy

Active Publication Date: 2017-11-07
GUANGDONG UNIV OF TECH
View PDF4 Cites 41 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Existing recommendation systems are generally based on coordinated filtering algorithms. However, with the increase of user groups, the number of products and information have increased significantly, and the user behavior data for products is extremely sparse, and the accuracy of the recommendation system is low.

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
  • Information recommending method and device
  • Information recommending method and device
  • Information recommending method and device

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach

[0119] In parameter estimation, it is difficult to directly obtain the parameter u i , v j . The EM algorithm (ExpectationMaximization, expectation maximization algorithm) can be used for parameter estimation, that is, the remaining parameter variables are fixed, and a certain parameter variable is optimized, namely:

[0120] u i ←(VC i V T +λ U I k ) -1 (VC i R i +λ U Net u (Z,S i ));

[0121] v j ←(UC j u T +λ V I k ) -1 UC j R j ;

[0122] in, for user u i , C i for C ij The diagonal matrix, j=1,2,..,J, J is the diagonal element, R i for for commodity v j , C i and R i The definition of u is the same as above i Definitions are similar. The above formula reflects the relationship between the user’s potential social relationship features and the user’s feature vector u learned through the deep convolutional neural network of the user’s social relationship i The influence of , where λ U It is used to weigh the influence of social relations. ...

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

An embodiment of the invention discloses an information recommending method and device, wherein the method includes: selecting K neighboring users from a social relation network by learning embedding feature vectors of users in the network according to node2vec algorithm, and extracting potential features of a current user from an embedding feature matrix generated from the K neighboring users according to CNN (convolutional neural network) algorithm; subjecting a historical information rating matrix to iterative alternating operation via a preset algorithm according to the potential features so as to obtain a user feature matrix and information feature matrix of the current user; performing information recommending for the current user according to the user feature matrix and / or information feature matrix. Deep potential features of a current user can be mined so that information recommending efficiency and accuracy are improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of information processing, and in particular, to an information recommendation method and device. Background technique [0002] With the rapid development of cloud computing and big data technology, the data shows explosive growth. It is becoming more and more difficult for users to find the information they are interested in from the massive amount of information, and it has become an urgent problem for those skilled in the art to accurately recommend the required information for users. [0003] Existing recommendation systems are generally based on coordinated filtering algorithms. However, with the increase of user groups, the number of products and information have increased significantly, and the user behavior data for products is extremely sparse, and the accuracy of the recommendation system is low. Contents of the invention [0004] The purpose of the embodiments of the prese...

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): G06F17/30G06Q50/00
CPCG06F16/9535G06Q50/01
Inventor 刘文印范文琦李青
Owner GUANGDONG UNIV OF TECH
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