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KDD
2006
ACM
183views Data Mining» more  KDD 2006»
16 years 8 months ago
Discovering interesting patterns through user's interactive feedback
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
16 years 8 months ago
Formulating distance functions via the kernel trick
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Gang Wu, Edward Y. Chang, Navneet Panda
KDD
2004
ACM
114views Data Mining» more  KDD 2004»
16 years 8 months ago
Mining reference tables for automatic text segmentation
Automatically segmenting unstructured text strings into structured records is necessary for importing the information contained in legacy sources and text collections into a data ...
Eugene Agichtein, Venkatesh Ganti
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 8 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
16 years 8 months ago
Ordering patterns by combining opinions from multiple sources
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Pang-Ning Tan, Rong Jin