Khairil Imran Bin Ghauth

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A recommender system is a piece of software that helps users to identify the most interesting and relevant learning items from a large number of items. Recommender systems may be based on collaborative filtering (by user ratings), content-based filtering (by keywords), and hybrid filtering (by both collaborative and content-based filtering). Recommender(More)
To improve website, we need to evaluate current usage of it. Web usage mining and statistical analysis are two ways to evaluate usage of website. The combination of web usage mining and statistical analysis gives more accurate information about web usage. Through web usage mining methods, graph mining covers complex web browsing behaviors such as parallel(More)
One of the anticipated challenges of today’s e-learning is to solve the problem of recommending from a large number of learning materials. In this study, we introduce a novel architecture for an e-learning recommender system. More specifically, this paper comprises the following phases i) to propose an e-learning recommender system based on content-based(More)
The growth of World Wide Web is incredible as it can be seen in present days. Users find it very difficult to extract useful and relevant information from the huge amount of information. The problems can be solved by Web Usage Mining which involves preprocessing, pattern discovery and pattern analysis. Preprocessing is an important process which converts(More)
This paper introduces a novel architecture for an e-learning recommender system which is based on good learners’ average ratings strategy and content-based filtering approach. The feasibility of the proposed system is conducted by comparing its performance against other recommender systems and an adaptive hypermedia system in order to measure the(More)
The ability to retrieve device capabilities provides huge potential in enhancing contents to user. In this paper, we propose service-based content adaptation platform (SCAP) that adapts content for display on mobile devices. It serves the objectives to provide adaptive content to user without direct user input; to provide an enhanced user experience by(More)
E-learning is emerging as the new paradigm of modern education. Most of the e-learning systems have limitations such as scarcity of content, lack of intelligent search and context sensitive personalization problems, which are the challenging tasks for researchers. This motivated the author to take up this problem and the method implemented through this work(More)
The success of Web technology has built e-Learning a common success way of education and training. To provide online automatic adaptive learning content , this paper suggest a framework for building such learning management system based upon MAS( Multi Agent System) , Semantic web ontology and learners preference knowledge base for content resource(More)