Web usage mining for UUM learning care using association rules

Ramli, Azizul Azhar (2004) Web usage mining for UUM learning care using association rules. Masters thesis, Universiti Utara Malaysia.


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The enormous content of information on the World Wide Web makes it obvious candidate for data mining research. Application of data milling techniques to the World Wide Web referred as Web mining where this term has been used in three distinct ways; Web Content Mining, Web Structure Mining and Web Usage Mining. E-Leaming is one of the Web based application where it will facing with large amount of data. In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. Web usage mining consists of three main phases, namely Data Preprocessing, Pattern Discovering and Pattern Analysis. Main resources, server log files become a set of raw data where it's must go through with all the Web usage mining phases to produce the final results — set of rides. With the powerful of data mining technique, Web usage mining approach has been combined with the basic Association Rules, Apriori Algorithm to optimize the content of the university E�Learning portal. Finally, this paper will present an overview of results with the analysis and Web administrator can use the findings for the suitable valuable actions.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Computer software
Depositing User: Mrs. Sabarina Che Mat
Date Deposited: 17 Jan 2023 03:38
Last Modified: 17 Jan 2023 03:38
URI: http://eprints.uthm.edu.my/id/eprint/8152

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