Personalized Recommendations in e-Learning System using Web Mining

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.