Chapter

Knowledge-Based Intelligent Information and Engineering Systems

Volume 3682 of the series Lecture Notes in Computer Science pp 964-971

Finding Closed Itemsets in Data Streams

  • Hai WangAffiliated withCarnegie Mellon UniversitySchool of Electronics & Information Engineering, Xi’an Jiaotong University
  • , Wenyuan LiAffiliated withCarnegie Mellon UniversityCentre for Advanced Information Systems, Nanyang Technological University
  • , Zengzhi LiAffiliated withCarnegie Mellon UniversitySchool of Electronics & Information Engineering, Xi’an Jiaotong University
  • , Lin FanAffiliated withCarnegie Mellon UniversitySchool of Electronics & Information Engineering, Xi’an Jiaotong University

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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.