Pattern-Oriented Clustering of Web Transactions
نویسندگان
چکیده
We propose a method for clustering web transaction data based on the idea that patterns generated within a cluster are similar to each other and different from patterns generated from other clusters. To do this, we define the difference between clusters and the similarity of transactions within a cluster using the notion of itemsets. A preliminary experiment on user-centric web browsing data demonstrates that our method is promising in clustering web transaction data and can discover interesting clusters among user transactions on the Web.
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تاریخ انتشار 2003