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» Mining Association Rules: Anti-Skew Algorithms
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HIPC
2003
Springer
14 years 24 days ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
KDD
2002
ACM
166views Data Mining» more  KDD 2002»
14 years 8 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu
KDD
2002
ACM
196views Data Mining» more  KDD 2002»
14 years 8 months ago
Comparing Two Recommender Algorithms with the Help of Recommendations by Peers
Abstract. Since more and more Web sites, especially sites of retailers, offer automatic recommendation services using Web usage mining, evaluation of recommender algorithms has bec...
Andreas Geyer-Schulz, Michael Hahsler
HICSS
2003
IEEE
171views Biometrics» more  HICSS 2003»
14 years 26 days ago
Improving the Efficiency of Interactive Sequential Pattern Mining by Incremental Pattern Discovery
The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
Ming-Yen Lin, Suh-Yin Lee
FSKD
2005
Springer
90views Fuzzy Logic» more  FSKD 2005»
14 years 1 months ago
Direct Candidates Generation: A Novel Algorithm for Discovering Complete Share-Frequent Itemsets
The value of the itemset share is one way of evaluating the magnitude of an itemset. From business perspective, itemset share values reflect more the significance of itemsets for m...
Yu-Chiang Li, Jieh-Shan Yeh, Chin-Chen Chang