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Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype

The search engine has become one of the most popular tools used on the Internet. Most of the existing search engines locate information based on queries consisting of a small number of keywords provided by the users. Although those search engines can query their databases and retrieve documents in a timely manner, the quality of the results is often unsatisfactory. This problem, based on previous studies and our observation, is partially due to the lack of semantic interpretation of a search request, as well as the user's incapability to precisely express their information need in a short query. In this research, we propose a conceptual framework that classifies various types of context in a Web search environment and present a new semantics-based approach that disambiguates user queries by analyzing the "relationship" context associated with query concepts.Our multi-methodological research approach includes: (i) building a context framework by categorizing different types of context; (ii) proposing a search mechanism that discovers and utilizes semantic relationships among query terms; (iii) demonstrating the practical implications of our proposed model using a proof-of-concept prototype system; and (iv) evaluating the usefulness of "relationship" context through an experimental study. From a technical perspective, our approach integrates ideas from semantic network, ontology, and information retrieval techniques. The experimental study conducted in the medical domain shows that our approach is effective and outperforms an existing popular search engine on search tasks consisting of key semantic relationships.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/195285
Date January 2006
CreatorsZhang, Limin
ContributorsRam, Sudha, Zeng, Daniel, Ram, Sudha, Zeng, Daniel, Tanniru, Mohan, Kobourov, Stephen, Snodgrass, Richard
PublisherThe University of Arizona.
Source SetsUniversity of Arizona
LanguageEnglish
Detected LanguageEnglish
Typetext, Electronic Dissertation
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.

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