IPACT: Improved Web Page Recommendation System Using Profile Aggregation Based On Clustering of Transactions
Yahya AlMurtadha1, Md. Nasir Bin Sulaiman1, Norwati Mustapha1 & Nur Izura Udzir1 Show affiliations
- Department of Computer Science, Faculty of Computer Science and Information Technology, University Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia
American Journal of Applied Sciences, Volume 8, Issue 3, pp. 277–283 · doi.org/10.3844/ajassp.2011.277.283
Abstract
Problem statement: Recently, Web usage mining techniques have been widely used to build recommendation systems especially for anonymous users. Approach: Assigning the current user to the best web navigation profile with similar navigation activities will improve the ability of the prediction engine to produce a recommendation list then introduce it to the user. This study presents iPACT an improved recommendation system using Profile Aggregation based on Clustering of Transactions (PACT). Results: iPACT shows better prediction accuracy than the previous methods PACT and Hypergraph. Conclusion: The users’ interests change over time; hence an incremental and adaptive web navigation profiling is a key feature for the future works.
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AlMurtadha, Y., Sulaiman, M. N. B., Mustapha, N. & Udzir, N. I. (2011). IPACT: Improved Web Page Recommendation System Using Profile Aggregation Based On Clustering of Transactions. American Journal of Applied Sciences, 8(3), 277–283. https://doi.org/10.3844/ajassp.2011.277.283
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