DocumentCode :
2897675
Title :
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
Link To Document :
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