JOURNAL ARTICLE

Domain Ontology Driven Fuzzy Semantic Information Retrieval

S. RemiSherwin Varghese

Year: 2015 Journal:   Procedia Computer Science Vol: 46 Pages: 676-681   Publisher: Elsevier BV

Abstract

With the exponential growth in web content, the answers provided by traditional search engines by query specific keywords to content has resulted in markedly high recall and low precision. Semantic information retrieval can enhance the relevancy of search results by understanding search intention and the contextual meaning of terms as they are entered by the user. In this paper, a novel method for supporting semantic information retrieval is proposed by building a domain specific ontology. A prototype of a fuzzy semantic search engine is developed and the results are compared with that of a traditional search engine.

Keywords:
Computer science Information retrieval Ontology Domain (mathematical analysis) Fuzzy logic Artificial intelligence Natural language processing

Metrics

22
Cited By
4.09
FWCI (Field Weighted Citation Impact)
21
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing
Service-Oriented Architecture and Web Services
Physical Sciences →  Computer Science →  Information Systems

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