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Published
Jul 17, 2014
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Abstract

Personalization is a subclass of information filtering system that seek to predict the 'ratings' or 'preferences' that a user would give to an items, they had not yet considered, using a model built from the characteristics of an item (content-based approaches or collaborative filtering approaches). Web mining is an emerging field of data mining used to provide personalization on the web. It consist three major categories i.e. Web Content Mining, Web Usage Mining, and Web Structure Mining. In this paper, a simplified Personalized Recommendation System using web usage mining and content mining is proposed to provide personalized search results to learners. The web usage mining and content mining technologies are used for system implementation aim to identify personalized recommendations. Basically, It consist four major steps to construct personalized recommendations are Data Collection, Data Processing, Data Analysis, and Output Generation. The proposed architecture in this paper is implemented using .Net technology to achieve system goals.


Keywords: Recommendations, Web Usage Mining, Association Rule Mining, Clustering, Lingo.

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Author Biographies

Namdev Ashok Anwat, Matoshri College of Engineering and Research Center, Nashik. University of Pune, Pune.

PG Student

Department of Computer Engineering

Mrs. Varsha Patil, Matoshri College of Engineering and Research Center, Nashik Near odha gaon, Eklahare, Nashik, Maharashtra - 422105, India University of Pune, Pune

Department of Computer Engineering
How to Cite
Anwat, N. A., & Patil, M. V. (2014). Personalized Recommendations in e-Learning System using Web Mining. International Journal of Emerging Trends in Science and Technology, 1(05). Retrieved from https://igmpublication.org/ijetst.in/index.php/ijetst/article/view/216

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