Paper Title:
Data Stream Frequent Closed Item Sets Mining Based on Fast Sliding Window
  Abstract

According to the mobility and continuity of the flow of data streams,this paper presents an algorithm called NSWR to mine the frequent item sets from a fast sliding window over data streams and it meets people’s needs of getting the frequent item sets over data that recently arrive. NWSR, using an effective bit-sequence representation of items based on the data stream sliding window, helps to store data; to support different support threshold value inquiry through hash-table-based frequent closed item sets results query method; to offer screening method based on the classification of closed item sets for reducing the number of item sets that need closure judgments, effectively reducing the computational complexity. Experiments show that the algorithm has better time and space efficiency.

  Info
Periodical
Edited by
Han Zhao
Pages
3702-3707
DOI
10.4028/www.scientific.net/AMM.130-134.3702
Citation
Z. H. Chen, J. Luo, "Data Stream Frequent Closed Item Sets Mining Based on Fast Sliding Window", Applied Mechanics and Materials, Vols. 130-134, pp. 3702-3707, 2012
Online since
October 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Zhong Ping Zhang, Yong Xin Liang
Abstract:This paper proposes a new data stream outlier detection algorithm SODRNN based on reverse nearest neighbors. We deal with the sliding window...
1032
Authors: Hai Feng Li, Ning Zhang
Chapter 1: Transportation & Service Science
Abstract:Maximal frequent itemsets are one of several condensed representations of frequent itemsets, which store most of the information contained in...
21
Authors: Dong Wang, Shi Huan Xiong
Chapter 8: Nanomaterials and Nanomanufacturing
Abstract:The learning sequence is an important factor of affecting the study effect about incremental Bayesian classifier. Reasonable learning...
1455
Authors: Jun Tan
Chapter 12: Computer-Aided Design and Applications in Industry and Civil Engineering
Abstract:Online mining of frequent closed itemsets over streaming data is one of the most important issues in mining data streams. In this paper, we...
2910
Authors: Hui Wang
Chapter 5: Numerical Methods, Computation Methods and Algorithms for Modeling, Simulation and Optimization, Data Mining and Data Processing
Abstract:We present a new algorithm for mining maximal frequent itemsets, MaxMining, from big transaction databases. MaxMining employs the depth-first...
1765