Information Retrieval on Web: Ontology Based Vs Traditional Search Engines
Disha Grover1, Barjesh Kochar2
1Disha Grover, IT Department, Jagan Institute Of Management Studies, Delhi, India.
2Dr Barjesh Kochar, IT Department, Vivekananda Institute of Professional Studies, Delhi, India.
Manuscript received on 15 August 2019. | Revised Manuscript received on 25 August 2019. | Manuscript published on 30 September 2019. | PP: 901-903 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4085098319/19©BEIESP | DOI: 10.35940/ijrte.C4085.098319
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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: Information Retrieval has become the buzzword in the today’s era of advanced computing. The tremendous amount of information is available over the Internet in the form of documents which can either be structured or unstructured. It is really difficult to retrieve relevant information from such large pool. The traditional search engines based on keyword search are unable to give the desired relevant results as they search the web on the basis of the keywords present in the query fired. On contrary the ontology based semantic search engines provide relevant and quick results to the user as the information stored in the semantic web is more meaningful. The paper gives the comparative study of the ontology based search engines with those which are keyword based. Few of both types have been taken and same queries are run on each one of them to analyze the results to compare the precision of the results provided by them by classifying the results as relevant or non-relevant.
Keywords: Information Retrieval, Ontology, Semantic Web
Scope of the Article: Vision-Based Applications.