PRIOR ONTOLOGY SELECTION AND QUERY TRANSLATION FOR INFORMATION SEARCH

Poornima N; Shivam Agrawal; Shivam Agrawal; Saleena B; Saleena B

doi:10.22159/ajpcr.2017.v10s1.23490

Authors

Poornima N Department of , School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India.
Shivam Agrawal Department of , School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India.
Shivam Agrawal Department of , School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India.
Saleena B Department of , School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India.
Saleena B Department of , School of Computing Science and Engineering, VIT University, Chennai, Tamil Nadu, India.

DOI:

https://doi.org/10.22159/ajpcr.2017.v10s1.23490

Keywords:

Semantics, Data retrieval, Ontology, Resource Description Framework, SPARQL

Abstract

Objective: Most of the current search engines follow informal keyword based search. Finding the user intention and improving the relevancy of results are the major issues faced by the current traditional keyword based search. Targeting to solve the problems of traditional search and to boost the retrieval process, a framework for semantic based information retrieval is planned.

Methods: Social and wine ontologies are used to find the user intention and retrieving it. User's natural language queries are translated into SPARQL (SPARQL Protocol and Resource Description Framework query language) query for finding related items from those ontologies.

Results: The proposed method makes a significant improvement over traditional search in terms of some searches required for searching a particular number of pages using performance graph.

Conclusion: Semantic based search can understand the user intention and gives better results than traditional search.

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References

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Available from: https://www.w3.org/TR/rdf-sparql-query.