A Soft Set-based Co-occurrence for Clustering Web User Transactions
Abstract: 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.
Author: Edi Sutoyo
Journal Code: jptkomputergg170049
