Browsing by Author "Mohd Salihin Bin Ngadiman"

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    Rough fuzzy approach for web usage mining
    (2006) Siriporn Chimphlee; Naomie Salim; Mohd Salihin Bin Ngadiman; Witcha Chimphlee; Surat Srinoy; S. Chimphlee; Faculty of Science and Technology, Suan Dusit Rajabhat University, Dusit, Bangkok, 295 Rajasrima Rd, Thailand; email: siriporn_chi@dusit.ac.th
    Web usage mining is a new subfield of data mining research. It aims at discovery of trends and regularities in web users' access patterns. In the past few years, web usage mining techniques have grown rapidly together with the explosive growth of the web, both in the research and commercial areas. A challenge in web classification is how to deal with the high dimensionality of the feature space. This paper applies the concept of rough fuzzy approach for classification in web usage mining tasks after we present Independent Component Analysis (ICA) for feature. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users.
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    Using association rules and Markov model for predict next access on Web usage mining
    (2006) Siriporn Chimphlee; Naomie Salim; Mohd Salihin Bin Ngadiman; Witcha Chimphlee
    Predicting the next request of a user as visits Web pages has gained importance as Web-based activity increases. A large amount of research has been done on trying to predict correctly the pages a user will request. This task requires the development of models that can predicts a user's next request to a web server. In this paper, we propose a method for constructing first-order and second-order Markov models of Web site access prediction based on past visitor behavior and compare it association rules technique. In these approaches, sequences of user requests are collected by the session identification technique, which distinguishes the requests for the same web page in different browses. We report experimental studies using real server log for comparison between methods and show that degree of precision. © 2006 Springer.