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» Supervised Feature Extraction Using Hilbert-Schmidt Norms
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WEBI
2005
Springer
15 years 5 months ago
A Semi-Supervised Document Clustering Algorithm Based on EM
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
Leonardo Rigutini, Marco Maggini
BMCBI
2010
111views more  BMCBI 2010»
14 years 11 months ago
Protein sequences classification by means of feature extraction with substitution matrices
Background: This paper deals with the preprocessing of protein sequences for supervised classification. Motif extraction is one way to address that task. It has been largely used ...
Rabie Saidi, Mondher Maddouri, Engelbert Mephu Ngu...
INTERSPEECH
2010
14 years 6 months ago
Exploring speaker characteristics for meeting summarization
In this paper, we investigate using meeting-specific characteristics to improve extractive meeting summarization, in particular, speaker-related attributes (such as verboseness, g...
Fei Liu, Yang Liu
132
Voted
ACL
2010
14 years 9 months ago
Open Information Extraction Using Wikipedia
Information-extraction (IE) systems seek to distill semantic relations from naturallanguage text, but most systems use supervised learning of relation-specific examples and are th...
Fei Wu 0003, Daniel S. Weld
110
Voted
ACL
2011
14 years 3 months ago
Rare Word Translation Extraction from Aligned Comparable Documents
We present a first known result of high precision rare word bilingual extraction from comparable corpora, using aligned comparable documents and supervised classification. We in...
Emmanuel Prochasson, Pascale Fung