Finding closed itemsets in data streams

Authors:
Hai Wang;Wenyuan Li;Zengzhi Li;Lin Fan
Affiliations:
School of Electronics & Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China;Centre for Advanced Information Systems, Nanyang Technological University, Singapore;School of Electronics & Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China;School of Electronics & Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2005

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Abstract

Closed itemset mining is a difficult problem especially when we consider the task in the context of a data stream. Compared to mining from a static transaction data set, the streaming case has far more information to track and far greater complexity to manage. In this paper, we propose a complete solution based on CLOSET+ algorithm to closed itemset mining in data streams. In data streams, bounded memory and one-pass constraint are expected. In our solution, these constraints are both taken into account.