An Approach for Semantic Information Retrieval from Ontology in Computer Science Domain
Ritika Bansal1, Sonal Chawla2
1Ritika Bansal, Research Scholar, Department of Computer Science and Applications, Panjab University & Assistant Professor, M.C.M. D.A.V. College for Women, Chandigarh, India.
2Sonal Chawla, Associate Professor & Chairperson, Department of Computer Science and Applications, Panjab University, Chandigarh, India.
Manuscript received on November 13, 2014. | Revised Manuscript received on November 27, 2014. | Manuscript published on December 30, 2014. | PP: 58-65  | Volume-4 Issue-2, December 2014. | Retrieval Number:  B3593124214/2013©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Ontology plays a pivotal role in exchange of information, use of knowledge and its re-use, shared and common understanding of a domain specific knowledge that can be communicated between people and across application systems which is the goal of semantic web. Ontology is used to capture knowledge about any domain of interest with the objective of incorporating the machine understandable data on the current human-readable web. Ontology is a broad term including a wide range of activities, complexities and issues in which Ontology Development is one of the most fundamental and significant concern[1]. There may be various methodologies or tools for ontology development. This paper has three main objectives. Firstly, it considers the computer science domain and demonstrates the development of Ontology in this domain using Protégé 3.4 Editor. Secondly, this paper focuses on the techniques and query language SPARQL for data retrieval from Ontology. Thirdly, this paper will discuss an approach for retrieving information from Ontology through natural language queries by demonstrating the layout of IRSCSD (Information retrieval system for computer science domain).
Keywords: Ontology, RDF, Semantic Searching, SPARQL, NLQ, Protégé, Jena API, Query.