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ICDM
2006
IEEE
132views Data Mining» more  ICDM 2006»
16 years 23 days ago
High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
Hassan H. Malik, John R. Kender
CIKM
2009
Springer
15 years 11 months ago
Probabilistic models for topic learning from images and captions in online biomedical literatures
Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and pro...
Xin Chen, Caimei Lu, Yuan An, Palakorn Achananupar...
PKDD
1999
Springer
106views Data Mining» more  PKDD 1999»
15 years 11 months ago
Heuristic Measures of Interestingness
When mining a large database, the number of patterns discovered can easily exceed the capabilities of a human user to identify interesting results. To address this problem, variou...
Robert J. Hilderman, Howard J. Hamilton
SDM
2004
SIAM
174views Data Mining» more  SDM 2004»
15 years 8 months ago
Classifying Documents Without Labels
Automatic classification of documents is an important area of research with many applications in the fields of document searching, forensics and others. Methods to perform classif...
Daniel Barbará, Carlotta Domeniconi, Ning K...
DATAMINE
1999
152views more  DATAMINE 1999»
15 years 6 months ago
Discovery of Frequent DATALOG Patterns
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...
Luc Dehaspe, Hannu Toivonen
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