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Leveraging Indexical Pragmatics (OFIP) for Search Engine: An Ontology- based Approach

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Title:Leveraging Indexical Pragmatics (OFIP) for Search Engine: An Ontology- based Approach
Authors:Liu, Dapeng
Yoon, Victoria Y
Keywords:Data, Text, and Web Mining for Business Analytics
Decision Analytics, Mobile Services, and Service Science
Information extraction, Indexical pragmatics, Ontology, Search relevance
Date Issued:08 Jan 2019
Abstract:The relevance of search results is an important indicator of information retrieval performance. A domain-specific Search Engine (SE), distinct from a general web SE, focuses on a specific segment of online content and may increase search results relevance. Traditional methods to improve domain-specific SE precision heavily depend on query expansion, lexical analysis of texts, and large amounts of training data. These methods suffer from limited effectiveness and efficiency because expanded query terms and coarse language features bring in uncontrollable complexity and increase dimensionality. Our design, leveraging the integrated power of computational syntax, semantics, and indexical pragmatics, proposes an ontology-driven framework that is tailored to work in a dynamic Internet environment without large amounts of manually annotated training data. This article presents our design, that is essential for building a domain-specific SE, and its instantiation in the terrorism domain.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/59554
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.140
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Data, Text, and Web Mining for Business Analytics


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