An immune-based model for Web data mining

Author

Feng, Wang ; Li, Xuwei ; Hong, Zhu

Author_Institution

Comput. Coll., Sichuan Univ., Chengdu, China

fYear

2005

fDate

4-8 April 2005

Firstpage

547

Lastpage

551

Abstract

This paper presents an immune-based model for Web data mining, in which the rule library and statistic dictionary are used to build search schemas, and data from different sources are wrapped to XML. By using Web content mining and Web structure mining, data are abstracted to mediated schemas and then compared with search schemas. As the information about Web page content and its links are optimized, the traditional search strategy based on keyword matching can be improved. At the same time, many ideas of immune system are introduced to increase the search efficiency. Now many Web data mining system using immune approaches by Andrew Seeker, Alex A. Freitas, and Jon Timmis, (2003), H.A. Abbass, R.A. Sarker, and C.S. Newton (2001) are concerned with data clustering, while immunity is mainly used for data processing after clustering in this model.

Keywords

Internet; XML; data mining; information retrieval; Web content mining; Web data mining; Web page content; Web structure mining; XML; data clustering; immune-based model; keyword matching; rule library; statistic dictionary; Biological system modeling; Data mining; Dictionaries; Educational institutions; Filters; Immune system; Libraries; Statistics; Uniform resource locators; XML;

fLanguage

English

Publisher

ieee

Conference_Titel

Autonomous Decentralized Systems, 2005. ISADS 2005. Proceedings

Print_ISBN

0-7803-8963-8

Type

conf

DOI

10.1109/ISADS.2005.1452133

Filename

1452133