Personalized Web Page Recommendation Using Ontology
Main Article Content
Abstract
In this network era, Web Page Recommendation and web page Recommendation systems can take advantage of semantic network reasoning-capabilities to overcome common limitations of current systems and improve the recommendations’ quality. This paper presents a personalized-web-recommendation system, a system that makes use of representations of items and user-profiles based on ontology in order to provide semantic applications with personalized services. The recommender uses domain ontology to enhance the personalization: on the other hand, user’s interests are modeled in a more effective and accurate way by applying a domain-based inference method; on the other hand, the stemmer algorithm used by our content-based filtering approach, which provides a measure of the affinity between an item and a user, is enhanced by applying a semantic similarity method. Web Usage Mining plays an important role in web page recommender systems and web personalization system. In this paper, we propose an effective personalized web recommendation system based on ontology and Web Usage Mining. The proposed approach integrates semantic knowledge into Web Usage Mining and personalization processes.
DOI: 10.17762/ijritcc2321-8169.150719
DOI: 10.17762/ijritcc2321-8169.150719
Article Details
How to Cite
, A. P. P. S. S. (2015). Personalized Web Page Recommendation Using Ontology. International Journal on Recent and Innovation Trends in Computing and Communication, 3(7), 4431–4436. https://doi.org/10.17762/ijritcc.v3i7.4667
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Articles