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» Mining Soft-Matching Rules from Textual Data
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KDD
2003
ACM
113views Data Mining» more  KDD 2003»
14 years 8 months ago
Mining unexpected rules by pushing user dynamics
Unexpected rules are interesting because they are either previously unknown or deviate from what prior user knowledge would suggest. In this paper, we study three important issues...
Ke Wang, Yuelong Jiang, Laks V. S. Lakshmanan
BNCOD
2003
127views Database» more  BNCOD 2003»
13 years 9 months ago
Performance Evaluation and Analysis of K-Way Join Variants for Association Rule Mining
Data mining aims at discovering important and previously unknown patterns from the dataset in the underlying database. Database mining performs mining directly on data stored in r...
P. Mishra, Sharma Chakravarthy
KDD
1998
ACM
131views Data Mining» more  KDD 1998»
13 years 11 months ago
Interestingness-Based Interval Merger for Numeric Association Rules
We present an algorithm for mining association rules from relational tables containing numeric and categorical attributes. The approach is to merge adjacent intervals of numeric v...
Ke Wang, Soon Hock William Tay, Bing Liu
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
14 years 8 months ago
Stochastic processes and temporal data mining
This article tries to give an answer to a fundamental question in temporal data mining: "Under what conditions a temporal rule extracted from up-to-date temporal data keeps i...
Paul Cotofrei, Kilian Stoffel
IJAR
2011
118views more  IJAR 2011»
12 years 11 months ago
A sequential pattern mining algorithm using rough set theory
Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns in time se...
Ken Kaneiwa, Yasuo Kudo