Abstract
Clustering faces several additional challenges, compared to traditional applications. The clusters tend to have imprecise boundaries and uncertainty. As a consequence of this uncertainty, we can highlight some challenges for web mining related to many problems such as: forming of clusters, the high computational complexity. Rough set theory has been used for clustering web user transactions, while managing uncertainty in clustering process. However, it suffers from high computational complexity. In this paper, we propose a framework for web clustering based on soft set theory with emphasis on reducing computational complexity.
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Acknowledgements
This work is supported by University of Malaya High Impact Research Grant no vote UM.C/625/HIR/MOHE/SC/13/2 from Ministry of Higher Education Malaysia.
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Sutoyo, E., Yanto, I.T.R., Saadi, Y., Chiroma, H., Hamid, S., Herawan, T. (2019). A Framework for Clustering of Web Users Transaction Based on Soft Set Theory. In: Abawajy, J., Othman, M., Ghazali, R., Deris, M., Mahdin, H., Herawan, T. (eds) Proceedings of the International Conference on Data Engineering 2015 (DaEng-2015) . Lecture Notes in Electrical Engineering, vol 520. Springer, Singapore. https://doi.org/10.1007/978-981-13-1799-6_32
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DOI: https://doi.org/10.1007/978-981-13-1799-6_32
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