A Soft Set-based Co-occurrence for Clustering Web User Transactions
Edi Sutoyo, Iwan Tri Riyadi Yanto, Rd Rohmat Saedudin, Tutut Herawan
Web transaction clustering of webpages is important yet a challenging web mining problem. This is due to uncertainty to form clusters. Rough set theory has been utilized for clustering web user transactions, while managing uncertainty in clustering process. However, it suffers from high computational complexity and low cluster purity. In this paper, we propose a soft set approach for clustering web user transactions. Unlike rough set approach that uses similarity approach, the novelty of this approach uses a co-occurrence approach of soft set. We compare the proposed approach and rough set approaches on computational complexity and cluster purity. The results show that the proposed soft set approach achieves lower computational complexity with the improvement of more than 100% and higher cluster purity as compared to rough set-based approaches.
Clustering; Web user transactions; Rough set theory; Soft set theory