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KDD
1998
ACM
118views Data Mining» more  KDD 1998»
15 years 10 months ago
A Belief-Driven Method for Discovering Unexpected Patterns
Several pattern discovery methods proposed in the data mining literature have the drawbacks that they discover too many obvious or irrelevant patterns and that they do not leverag...
Balaji Padmanabhan, Alexander Tuzhilin
KDD
2006
ACM
147views Data Mining» more  KDD 2006»
16 years 6 months ago
Summarizing itemset patterns using probabilistic models
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Chao Wang, Srinivasan Parthasarathy
ICDM
2009
IEEE
155views Data Mining» more  ICDM 2009»
16 years 1 months ago
A Contrast Pattern Based Clustering Quality Index for Categorical Data
Since clustering is unsupervised and highly explorative, clustering validation (i.e. assessing the quality of clustering solutions) has been an important and long standing researc...
Qingbao Liu, Guozhu Dong
DMKD
2004
ACM
127views Data Mining» more  DMKD 2004»
15 years 11 months ago
Discovering spatial patterns accurately with effective noise removal
Cluster analysis is a common approach to pattern discovery in spatial databases. While many clustering techniques have been developed, it is still challenging to discover implicit...
Yu Qian, Kang Zhang
KDD
2006
ACM
175views Data Mining» more  KDD 2006»
16 years 6 months ago
A mixture model for contextual text mining
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Qiaozhu Mei, ChengXiang Zhai