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

False comment group division method based on spectral clustering

A spectral clustering and group technology, applied in the field of data mining, can solve the problem of poor detection effect of fake comment groups, and achieve the effect of universality, good division effect and improved accuracy.

Active Publication Date: 2020-02-04
GUANGDONG UNIV OF TECH
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the defect of poor detection effect on false comment groups described in the above-mentioned prior art, the present invention provides a method for dividing false comment groups based on spectral clustering

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
  • False comment group division method based on spectral clustering
  • False comment group division method based on spectral clustering
  • False comment group division method based on spectral clustering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] This embodiment provides a method for grouping false comments based on spectral clustering, such as figure 1 As shown, the method includes the following steps:

[0056] S1: Collect and clean the comment data of the e-commerce platform; the metadata used includes: user id, comment id, product id, rating, and the number of interaction behaviors of comments (such as: being "liked" by other users, being "liked" by other users) found useful", "interesting" by other users, etc.);

[0057] Among them, metadata is data used to define data. Review data is data of many dimensions collected from e-commerce platforms, including fields such as user id, comment time, rating, etc. Each item here, such as "user id" and "comment time", is a piece of metadata. Through the description of the metadata, the information of a comment can be restored. In this example, some data items (metadata) of a comment are selected, such as "comment time" is not used.

[0058] S2: Based on the metadat...

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 a false comment group division method based on spectral clustering. The method comprises the steps of S1, collecting and cleaning comment data of an e-commerce platform; Ss2,based on the metadata in the step S1, calculating five similarity indexes including a'common comment frequency ', a'score similarity of the same commodity', a'user interaction frequency ', a'user positive score proportion' and a'user negative score proportion ', and measuring the similarity of the score proportion between the two users by using an Euclidean distance; s3, constructing a weighted reviewer graph; s4, dividing the adjacent matrix to obtain a plurality of groups; and S5, further judging the categories of the divided groups manually by selecting reasonable analysis indexes and proper thresholds. According to the method, the behavior similarity between the users is reflected more accurately, and the accuracy of a subsequent division algorithm is improved; and the method has a better division effect on the weighted reviewer graph and is more universal.

Description

technical field [0001] The present invention relates to the technical field of data mining, and more specifically, to a method for grouping false comments based on spectral clustering. Background technique [0002] With the rapid development of the Internet, the emergence of e-commerce platforms has changed people's consumption patterns in various aspects such as shopping, traveling, and dining. In the transaction process of the e-commerce platform, service or product reviews play a key role in the user's purchase decision-making behavior. Products with more positive reviews and more authentic products are more favored by users. The willingness to buy is low. In recent years, with the diversified development of e-commerce platforms and the intensification of market competition, many unscrupulous merchants will use various means to obtain more false positive reviews or give false negative reviews to competitors. Traditional methods such as sellers obtaining higher-than-aver...

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): G06K9/62G06Q30/00G06Q30/02
CPCG06Q30/0185G06Q30/0282G06F18/23213G06F18/22Y02D10/00
Inventor 王帮海叶子成
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