A Data Mining Algorithm of Frequent Pattern for Data Flow Based on Landmark Window

  • Chunsheng Zhang
  • Liyan Zhuang
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 124)

Abstract

According to the fact that data flow have the characteristics of large volume of data and real-time processing, adopting landmark window pattern, and overcoming the shortcoming of sliding window pattern and decaying window pattern such as information loss, a representation method of the transaction two-tuple based data flow is proposed. The article proposes the concept of data flow base, and obtains the transaction two-tuple by real-time scanning one time for data flow. Whether the scale of data flow is how large or not, the number of the transaction two-tuple will not exceed data flow base, if the value range of the attribute of data flow is distributed rationally, then the whole two-tuple can completely in memory, and the two-tuple is stored using the hash table. This scheme improves the speed of data mining, and does without losing the basic information of data flow, and has certain practicability and reliability.

Keywords

Data Stream Association Rule Hash Table Frequent Itemsets Data Mining Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chunsheng Zhang
    • 1
  • Liyan Zhuang
    • 1
  1. 1.College of Computer Science and TechnologyInner Mongolia University for NationalitiesTongliaoChina

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