Semantic-based Recommendation Tool for Library Management System using Domain Specific Ontology
Priya. P1, P. Velmurugan2
1Priya. P*, Assistant Professor, Department of Computer Science and Engineering, BIET, Hyderabad, Telangana, India.
2Dr. P. Velmurugan, Associate Professor, Department of Computer Science and Engineering, BIET, Hyderabad, Telangana, India.
Manuscript received on 04 August 2019. | Revised Manuscript received on 14 August 2019. | Manuscript published on 30 September 2019. | PP: 3755-3760 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5236098319/2019©BEIESP | DOI: 10.35940/ijrte.C5236.098319
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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: Semantic search plays a vital role for improving the output of information retrieval in today’s scenario. Users those who want to find the necessary information always feel comfortable to submit queries based on related keywords to the search engine. But, the major drawback of submitting keyword query is ambiguity. So, we are moving to semantic based search. Many traditional approaches like semantic search depending on ontology encourages user to type a formal language query. Most of the novice users are not aware of formal query languages. To resolve the above drawback and enhance the retrieval effectiveness, a semantic based recommendation tool using domain specific ontology is proposed. And also to solve the limitations of usability, a query interface has to be provided to the users in which the users can enter the natural language query. To implement this semantic based recommendation tool, a domain-specific ontology is used through which accurate search results can be achieved. This Query Recommendation tool is proposed for Library Management System which uses Library Ontology for Query Recommendation. This tool compares the input query given by the user related to Library with the Library ontology and other possible queries which are related to the user query are generated from the ontology based on different entities and relationship. The queries which are extracted from the ontology using entities and properties along with query log are recommended alternative to the user’s initial query. Since, the queries are extracted based on the semantics by which the concepts related to the user query are revealed, more relevant information is retrieved which leads to user satisfaction.
Keywords: Domain ontology, Knowledgebase, Query Augmentation, Semantic web, SPARQL.
Scope of the Article: Time and Knowledge Management Tools