Kuo-Chuan Huang

Enriching Ontology for Deep Web Search

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 users search terms only, with the Web sites found when using additional ontology-based search terms. Experiments suggest that the ontology plus instancesapproach results in more relevant Web sites among the first 100 hits.

Assessment for Ontology-Supported Deep Web Search

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.