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» A novel feature selection algorithm for text categorization
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ICAIL
2003
ACM
14 years 2 months ago
Concept Extraction from Legal Cases: The Use of a Statistic of Coincidence
Effective retrieval of court decisions is important. Automatically identifying legal concepts in the decision texts would be very helpful. In this paper we investigate how a stat...
Marie-Francine Moens, Roxana Angheluta
CIKM
2010
Springer
13 years 7 months ago
Context modeling for ranking and tagging bursty features in text streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
14 years 9 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
DATAMINE
2006
97views more  DATAMINE 2006»
13 years 8 months ago
Reinforcing Web-object Categorization Through Interrelationships
Existing categorization algorithms deal with homogeneous Web objects, and consider interrelated objects as additional features when taking the interrelationships with other types o...
Gui-Rong Xue, Yong Yu, Dou Shen, Qiang Yang, Hua-J...
ICMCS
2009
IEEE
126views Multimedia» more  ICMCS 2009»
13 years 6 months ago
Sort-Merge feature selection and fusion methods for classification of unstructured video
We explore the problem of rapid automatic semantic tagging of video frames of unstructured (unedited) videos. We apply the Sort-Merge algorithm for feature selection on a large (&...
Mitchell J. Morris, John R. Kender