Finding Closed Itemsets in Data Streams

  • Hai Wang
  • Wenyuan Li
  • Zengzhi Li
  • Lin Fan
Conference paper

DOI: 10.1007/11552451_133

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3682)
Cite this paper as:
Wang H., Li W., Li Z., Fan L. (2005) Finding Closed Itemsets in Data Streams. In: Khosla R., Howlett R.J., Jain L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science, vol 3682. Springer, Berlin, Heidelberg

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hai Wang
    • 1
  • Wenyuan Li
    • 2
  • Zengzhi Li
    • 1
  • Lin Fan
    • 1
  1. 1.School of Electronics & Information EngineeringXi’an Jiaotong UniversityXi’anChina
  2. 2.Centre for Advanced Information SystemsNanyang Technological UniversitySingapore

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