Name
Abstract | ||
|---|---|---|
Ontologies could play an important role in assisting users in their search for Web pages. This paper considers the problem of constructing domain ontologies that support users in their Web search efforts and that increase the number of relevant Web pages that are returned. To achieve this goal, this paper suggests combining Deep Web information, which consists of dynamically generated Web pages, which cannot be indexed by the existing automated Web crawlers, with ontologies. Improvements when finding deep Web sites returned by a search engine are assessed based on the framework formulated in this paper. Experimental results suggest that the proposed methods assist users in finding more relevant Web sites. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/CECandEEE.2008.117 | CEC/EEE |
Keywords | Field | DocType |
ontology-supported deep web search,relevant web site,deep web site,domain ontology,web pages,existing automated web crawler,web search efforts,web information,web search effort,semantic deep web,search engine,web search engine,deep web sites,deep web,web sites,relevant web page,ontologies (artificial intelligence),deep web information,search engines,web page,ontologies,indexing,web services,databases,data mining,indexation,web crawler | Web search engine,Static web page,World Wide Web,Web page,Computer science,Web standards,Data Web,Web modeling,Social Semantic Web,Web crawler | Conference |
ISSN | ISBN | Citations |
1530-1354 | 978-0-7695-3340-7 | 5 |
PageRank | References | Authors |
0.48 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yoo Jung An | 1 | 54 | 5.74 |
| Soon Ae Chun | 2 | 893 | 100.67 |
| Kuo-chuan Huang | 3 | 63 | 4.60 |
| James Geller | 4 | 33 | 5.08 |