A Multi-Agent Based Web Mining Model

Author

Geng, Zengmin ; Li, Xuefei ; Sun, Xiaodong

Author_Institution

Beijing Inst. of Fashion Technol., Beijing, China

fYear

2011

fDate

17-18 July 2011

Firstpage

1

Lastpage

4

Abstract

A multi-agent based Web mining model is designed for the improvement of the efficiency of keywords based search engine. The model divides mining task into several parallel agents which coordinately work together, and the mining efficiency is improved greatly. Evolving from HITS, algorithm named Grabber in the model removes Link Farm pages in the expansion of root set, makes anchor text similarity calculation when crawling link page, and chooses pages by a brief conceptual analysis of page content. With the overcoming of the shortcomings of only text analysis or link analysis, Grabber enhances the search engine in understanding the user interest and crawling more Web pages to meet the needs of the users.

Keywords

Internet; data mining; multi-agent systems; parallel processing; search engines; text analysis; Grabber algorithm; HITS; anchor text similarity calculation; keyword based search engine; link analysis; link farm pages; multiagent based Web mining model; page content; parallel agent; text analysis; Algorithm design and analysis; Computers; Databases; Kernel; Search engines; Text analysis; Web pages;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits, Communications and System (PACCS), 2011 Third Pacific-Asia Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4577-0855-8

Type

conf

DOI

10.1109/PACCS.2011.5990132

Filename

5990132