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» The Feature Importance Ranking Measure
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KDD
2007
ACM
179views Data Mining» more  KDD 2007»
15 years 3 months ago
Mining statistically important equivalence classes and delta-discriminative emerging patterns
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Jinyan Li, Guimei Liu, Limsoon Wong
77
Voted
COLING
2002
14 years 9 months ago
Automatic Text Categorization using the Importance of Sentences
Automatic text categorization is a problem of automatically assigning text documents to predefined categories. In order to classify text documents, we must extract good features f...
Youngjoong Ko, Jinwoo Park, Jungyun Seo
175
Voted
ICDE
2009
IEEE
158views Database» more  ICDE 2009»
15 years 11 months ago
KSpot: Effectively Monitoring the K Most Important Events in a Wireless Sensor Network
This demo presents a graphical user interface and ranking system, coined KSpot, for effectively monitoring the K highest-ranked answers to a query Q in a Wireless Sensor Network. K...
Panayiotis Andreou, Demetrios Zeinalipour-Yazti, M...
82
Voted
PAMI
2007
102views more  PAMI 2007»
14 years 9 months ago
Feature Subset Selection and Ranking for Data Dimensionality Reduction
—A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one ...
Hua-Liang Wei, Stephen A. Billings
AMR
2005
Springer
128views Multimedia» more  AMR 2005»
15 years 3 months ago
Ranking Invariance Based on Similarity Measures in Document Retrieval
Abstract. To automatically retrieve documents or images from a database, retrieval systems use similarity measures to compare a request based on features extracted from the documen...
Jean-François Omhover, Maria Rifqi, Marcin ...