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Ontology Based Web Page Recommendation System
A. Sivasangari1, S. Poonguzhali2, Immanuel Rajkumar3

1A. Sivasangari, Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India. 

2S. Poonguzhali, Sathyabama Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India.

3Immanuel Rajkumar, Sathyabama Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India.

Manuscript received on 13 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript Published on 26 July 2019 | PP: 1373-1376 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F12780486S419/19©BEIESP | DOI: 10.35940/ijitee.F1278.0486S419

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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 emerging web page development requires semantic applications with customized administrations. The proposed methodology presents a customized suggestion framework, which makes utilization of item representations and also client profiles created based on ontology. The domain ontology helps the recommender to improve the personalization: from one perspective, client’s interests are displayed in an increasingly powerful and precise route by applying an area based derivative technique; on the other side, the stemmer algorithm derived content- based filtering approach, gives an evaluation of resemblance among a thing and a client, upgraded by applying a semantic likeliness strategy. Recommender frameworks and web personalize were assumed by Web usage mining as a critical job. The proposed strategy is s successful framework dependent on ontology and web usage mining. Extricating highlights from web reports and building applicable ideas is the initial step of the methodology. At that point manufacture metaphysics for the site exploit the ideas and huge terms separated from reports. As per the semantic similitude of web archives to bunch them into various semantic topics, the distinctive subjects suggest diverse inclinations. The proposed methodology incorporates semantic information into Web Usage Mining and personalization process.

Keywords: Ontology, Filtering Method, Cluster.
Scope of the Article: Computer Science and Its Applications