NDLI: An ontology-driven approach to web search: analysis of its sensitivity to ontology quality and search tasks

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An ontology-driven approach to web search: analysis of its sensitivity to ontology quality and search tasks

Content Provider	ACM Digital Library
Author	Strasunskas, Darijus Tomassen, Stein L.
Abstract	An increasing number of recent information retrieval systems makes use of ontologies to help the users to detail queries and to come up with semantic representations of documents. A particular concern here is user-friendliness (usability) and scalability of those approaches for Web search purposes. In this paper, we present an approach where entities in an ontology are associated with domain terminology by feature vectors (FV). A FV reflects the semantic and linguistic neighbourhoods of a particular entity. The semantic neighbourhood is derived from an ontology and is based on related entities and specified properties, while linguistic neighbourhood is based on co-location of terms in a text corpus. Later, during the search process the FVs are used to filter and rerank the search results of the underlying search engine and thereby increasing the precision of the result. We elaborate on the approach and describe how the FVs are constructed. Then we report on a conducted evaluation where we analyse the sensitivity of the approach w.r.t. ontology quality and search tasks. Results indicate that the proposed approach and implemented prototype are able to improve the search results of a standard Web search engine. Furthermore, the analysis of the experiment data shows that the level of ontology specification is important for the quality of the FVs.
Starting Page	130
Ending Page	138
Page Count	9
File Format	PDF
ISBN	9781605586601
DOI	10.1145/1806338.1806368
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-12-14
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Feature vector construction Semantic search Ontology Ontology quality Web search
Content Type	Text
Resource Type	Article

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