Paper Title:
A Study of Association Rules Mining Algorithms Based on Adaptive Support
  Abstract

This paper presents an adaptive support for Boolean algorithm for mining association rules, the Algorithm does not require minimum support from outside, in the mining process of the algorithm will be based on user needs the minimum number of rules automatically adjust the scope of support to produce the specific number of rules, the algorithm number of rules for the user needs to generate the rules to a certain extent, reduce excavation time, avoid the artificial blindness specified minimum support. In addition, the core of the algorithm is using an efficient method of Boolean-type mining, using the logical OR, AND, and XOR operations to generate association rules, to avoided the candidate itemsets generated In the mining process, and only need to scan the database once, so the algorithm has a certain efficiency.

  Info
Periodical
Advanced Materials Research (Volumes 108-111)
Edited by
Yanwen Wu
Pages
436-440
DOI
10.4028/www.scientific.net/AMR.108-111.436
Citation
Y. S. He, P. Du, "A Study of Association Rules Mining Algorithms Based on Adaptive Support", Advanced Materials Research, Vols. 108-111, pp. 436-440, 2010
Online since
May 2010
Authors
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: Lu Na Byon, Jeong Hye Han
Abstract:As electronic commerce progresses, temporal association rules are developed by time to offer personalized services for customer’s interests....
287
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