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...

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Main Author: Zhang, Limin
Other Authors: Ram, Sudha
Language:EN
Published: The University of Arizona. 2006
Subjects:
Online Access:http://hdl.handle.net/10150/195285
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spelling ndltd-arizona.edu-oai-arizona.openrepository.com-10150-1952852015-10-23T04:42:29Z Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype Zhang, Limin Ram, Sudha Zeng, Daniel Ram, Sudha Zeng, Daniel Tanniru, Mohan Kobourov, Stephen Snodgrass, Richard context-based search Web information retrieval 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. 2006 text Electronic Dissertation http://hdl.handle.net/10150/195285 137356604 1602 EN Copyright © 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. The University of Arizona.
collection NDLTD
language EN
sources NDLTD
topic context-based search
Web information retrieval
spellingShingle context-based search
Web information retrieval
Zhang, Limin
Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype
description 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.
author2 Ram, Sudha
author_facet Ram, Sudha
Zhang, Limin
author Zhang, Limin
author_sort Zhang, Limin
title Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype
title_short Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype
title_full Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype
title_fullStr Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype
title_full_unstemmed Contextual Web Search Based on Semantic Relationships: A Theoretical Framework, Evaluation and a Medical Application Prototype
title_sort contextual web search based on semantic relationships: a theoretical framework, evaluation and a medical application prototype
publisher The University of Arizona.
publishDate 2006
url http://hdl.handle.net/10150/195285
work_keys_str_mv AT zhanglimin contextualwebsearchbasedonsemanticrelationshipsatheoreticalframeworkevaluationandamedicalapplicationprototype
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