Enriching ontology for deep web search
Document Type
Conference Proceeding
Publication Date
10-6-2008
Abstract
This paper addresses the problems of extracting instances from the Deep Web, enriching a domain specific ontology with those instances, and using this ontology to improve Web search. Extending an existing ontology with a large number of instances extracted from the Deep Web is an important process for making the ontology more usable for indexing of Deep Web sites. We demonstrate how instances extracted from the Deep Web are used to enhance a domain ontology. We show the contribution of the enriched ontology to Web search effectiveness. This is done by comparing the number of relevant Web sites returned by a search engine with a user's search terms only, with the Web sites found when using additional ontology-based search terms. Experiments suggest that the ontology plus instances approach results in more relevant Web sites among the first 100 hits. © 2008 Springer-Verlag Berlin Heidelberg.
Identifier
52949119228 (Scopus)
ISBN
[3540856536, 9783540856535]
Publication Title
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics
External Full Text Location
https://doi.org/10.1007/978-3-540-85654-2_9
e-ISSN
16113349
ISSN
03029743
First Page
73
Last Page
80
Volume
5181 LNCS
Recommended Citation
An, Yoo Jung; Chun, Soon Ae; Huang, Kuo Chuan; and Geller, James, "Enriching ontology for deep web search" (2008). Faculty Publications. 12625.
https://digitalcommons.njit.edu/fac_pubs/12625
