Unlock instant, AI-driven research and patent intelligence for your innovation.

Recommendation method based on co-occurrence analysis

A recommendation method and co-occurrence technology, applied in the field of recommendation systems, can solve problems such as low similarity accuracy, reduced recommendation result accuracy, insufficient extraction and reasonable representation of the scoring matrix in the construction of the scoring matrix, and reduce sparsity. , the effect of improving the recommendation accuracy

Active Publication Date: 2021-02-02
SHANXI UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The calculation of similarity is the core of collaborative filtering recommendation. When traditional collaborative filtering recommendation calculates the similarity between users and items, due to the common sparsity problem of user rating matrix, the calculated similarity is accurate. The accuracy is not high, thus reducing the accuracy of the recommendation results
At present, there are limitations and bottlenecks in improving the recommendation quality by predicting and interpolating the scoring matrix or dimensionality reduction. The reason is that the construction of the scoring matrix does not fully extract and reasonably represent the information contained in the scoring matrix.

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
  • Recommendation method based on co-occurrence analysis
  • Recommendation method based on co-occurrence analysis
  • Recommendation method based on co-occurrence analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034]The following describes the technical solutions in the embodiments of the present invention clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0035]In this embodiment, the recommendation method based on co-occurrence analysis is described in detail by taking movie ratings as an example, including the following steps:

[0036]Step 1. Data preparation: Collect data, and generate user-item rating matrix R=(rui )n×m , The scoring matrix, mark the scoring items that do not appear in the collected data as missing items

[0037]

[0038]Where n is the total number of users, m is the total number of projects, rui Rating the i-th movie for the u-th user

[0039]In the example, the original da...

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 belongs to the technical field of recommendation systems, and specifically relates to a recommendation method based on co-occurrence analysis. The invention relates to the proposal of two improved collaborative filtering recommendation methods (WCO_IBCF and MCO_IBCF). "Collaborative filtering recommendation" is a cross-field application. As an effective means of information filtering, the recommendation system especially focuses on using these technologies to improve the efficiency of information use. The application of co-occurrence latent semantic analysis theory and method in the field of recommendation system will improve the accuracy of recommendation results.

Description

Technical field[0001]The present invention belongs to the technical field of recommendation systems, and specifically relates to two recommendation methods based on co-occurrence analysis. The present invention relates to the proposal of two improved collaborative filtering recommendation methods (WCO_IBCF and MCO_IBCF). "Collaborative filtering recommendation" is a cross-domain approach. Application, recommendation system as an effective means of information filtering, especially focusing on using these technologies to improve the efficiency of information use. Co-occurrence latent semantic analysis theory and methods applied to the field of recommendation systems will improve the accuracy of recommendation results.Background technique[0002]Collaborative filtering recommendation technology is the most widely studied and applied technology in recommendation systems. By analyzing user interests, finding similar (interested) users of the specified user in the user group, combining the...

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 Patents(China)
IPC IPC(8): G06F16/9535
Inventor 牛奉高徐倩丽
Owner SHANXI UNIV