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Semantically Enhanced Information Retrieval System
Archana P. R.1, Nisha T. P.2, Leya Elizabeth Sunny3

1Archana P. R.*, Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, India.
2Nisha T. P., Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, India.
3Leya Elizabeth Sunny, Department of Computer Science and Engineering, Mar Athanasius College of Engineering, Kothamangalam, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 28, 2020. | Manuscript published on March 10, 2020. | PP: 966-972 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2656039520/2020©BEIESP | DOI: 10.35940/ijitee.E2656.039520
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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: The user gives an input query in classical In-formation Retrieval (IR) system, keywords of the query are extracted and also the matching documents that contain one or more words specified by the user are retrieved. Keyword searches have a tricky time distinguishing between words that are spelled in similar way but mean something different. This often leads to hits that are completely irrelevant to the query. Se-mantic search seeks to enhance search precision by understanding searcher intent and along with the contextual significance of terms, as they seem within the searchable information space, whether on the net or within a closed system, to get more applicable outcomes. Semantically Enhanced Information Retrieval(SEIR) system can overcome the constraints of keyword based search. SEIR can semantically enhance the IR process. Therein way, searching is finished considering the meanings of query in-stead of the literal strings. Such a research automates tasks that need conceptual understanding of objects. 
Keywords: Information Retrieval, Semantically Enhanced, Ontology, SPARQL Query, User Concept.
Scope of the Article: Information-Centric Networking