Improving category specific Web search by learning query modifications

Author

Glover, Eric J. ; Flake, Gary W. ; Lawrence, Steve ; Birmingham, William P. ; Kruger, Andries ; Giles, C. Lee ; Pennock, David M.

Author_Institution

NEC Res. Inst., Princeton, NJ, USA

fYear

2001

fDate

2001

Firstpage

23

Lastpage

32

Abstract

Users looking for documents within specific categories may have a difficult time locating valuable documents using general purpose search engines. We present an automated method for learning query modifications that can dramatically improve precision for locating pages within specified categories using Web search engines. We also present a classification procedure that can recognize pages in a specific category with high precision, using textual content, text location and HTML structure. Evaluation shows that the approach is highly effective for locating personal homepages and calls for papers. These algorithms are used to improve category specific search in the Inquirus 2 search engine

Keywords

Internet; classification; hypermedia markup languages; information resources; information retrieval; learning (artificial intelligence); search engines; HTML; Inquirus; Internet; Web search engines; category specific Web search; classification; documents; home pages; information retrieval; query modification learning; text location; textual content; Databases; HTML; Metasearch; National electric code; Search engines; Support vector machine classification; Support vector machines; Text recognition; Web pages; Web search;

fLanguage

English

Publisher

ieee

Conference_Titel

Applications and the Internet, 2001. Proceedings. 2001 Symposium on

Conference_Location

San Diego, CA

Print_ISBN

0-7695-0942-8

Type

conf

DOI

10.1109/SAINT.2001.905165

Filename

905165