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

Optimized selection method of user closest neighbor set of electronic commerce recommendation system

A nearest neighbor, recommendation system technology, applied in business, data processing applications, instruments, etc., can solve problems such as data sparse

Inactive Publication Date: 2016-10-12
TIANJIN UNIV
View PDF4 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to overcome the deficiencies in the prior art, and proposes an optimal selection method of the user's nearest neighbor set in the e-commerce recommendation system, which can not only improve the recommendation accuracy, but also solve the problems caused by data sparseness

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
  • Optimized selection method of user closest neighbor set of electronic commerce recommendation system
  • Optimized selection method of user closest neighbor set of electronic commerce recommendation system
  • Optimized selection method of user closest neighbor set of electronic commerce recommendation system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0013] Technical scheme of the present invention is:

[0014] (1) Collect the user-item rating data in the historical records, and establish the user-item rating matrix:

[0015]

[0016] (2) Calculate the similarity between the target user and other users. When calculating the similarity between other users and the target user, the common scoring items between the two are considered, and the classic Pearson similarity calculation method is adopted. The specific method is as follows:

[0017] s i m ( a , b ) = Σ i ∈ I a b ( R a i ...

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 relates to an optimized selection method of a user closest neighbor set of an electronic commerce recommendation system. The optimized selection method comprises the steps that user-project scoring data of a historical record is acquired, and a user-project scoring matrix is established; similarity between a target user and other users is calculated by adopting the Pearson similarity calculating method; for the users in a closest neighbor candidate set, an average error between the score of the user and the scores of the users in the set is calculated according to data of a common scoring item set shared by the user and the users in the above mentioned set, and then confidence level is calculated, when the average error is greater, the confidence level between the target user and the users in the set is smaller; K users having the high confidence levels are used to form the closest neighbor set of the target user, and in addition, 1<K<0. Accuracy of recommendation is improved.

Description

technical field [0001] The invention relates to a method for optimizing and selecting a user's nearest neighbor set in an e-commerce recommendation system. Background technique [0002] With the advent of the "Internet +" era and the rapid development of e-commerce, e-commerce websites use e-commerce recommendation systems to recommend product information to users, provide relevant suggestions, and assist users in making shopping decisions. As one of the traditional recommendation techniques, the collaborative filtering recommendation algorithm is simple and efficient, and has been widely and successfully applied in the recommendation system. [0003] Collaborative filtering recommendation methods are mainly divided into neighbor set-based and model-based recommendation methods. Among them, the recommendation method based on neighbor set is further divided into user-based and item-based methods. The core idea of ​​the user-based recommendation method is to recommend the it...

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): G06Q30/02G06Q30/06
CPCG06Q30/0255G06Q30/0631
Inventor 金志刚张子洋
Owner TIANJIN 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