Sequential Pattern Mining with Multiple Minimum Supports: a Tree Based Approach
碩士 === 國立中正大學 === 資訊管理學系 === 99 === Frequent pattern mining is an important data-mining method for determining correlations among items/itemsets. Since the frequencies for various items are always varied, specifying a single minimum support cannot exactly discover interesting patterns. To solve this...
Main Authors: | Yi-Chun Liao, 廖一寯 |
---|---|
Other Authors: | Ya-Han Hu |
Format: | Others |
Language: | en_US |
Published: |
2010
|
Online Access: | http://ndltd.ncl.edu.tw/handle/80254266005742387182 |
Similar Items
-
Mining Sequential Patterns with Multiple Minimum Supports
by: Chia-Sheng Lin, et al.
Published: (2003) -
An Asynchronous Periodic Sequential Pattern Mining Algorithm with Multiple Minimum Item Supports for Ad Hoc Networking
by: Xiangzhan Yu, et al.
Published: (2015-01-01) -
Mining Partial Periodic Patterns with Multiple Minimum Supports
by: Zhe-Min Lin, et al.
Published: (2005) -
Mining Partial Periodic Patterns with Multiple Minimum Supports
by: Zhe-Min Lin, et al.
Published: (2005) -
Applying Discretization and Multiple Minimum Supports for Mining Quantitative Association Rules
by: Guan-Jie Liao, et al.