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» Detecting Co-Derivative Documents in Large Text Collections
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KDD
2006
ACM
118views Data Mining» more  KDD 2006»
15 years 10 months ago
Reducing the human overhead in text categorization
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
Arnd Christian König, Eric Brill
88
Voted
LREC
2010
133views Education» more  LREC 2010»
14 years 11 months ago
Towards Sentiment Analysis of Financial Texts in Croatian
The paper presents results of an experiment dealing with sentiment analysis of Croatian text from the domain of finance. The goal of the experiment was to design a system model fo...
Zeljko Agic, Nikola Ljubesic, Marko Tadic
AND
2010
14 years 7 months ago
Reshaping automatic speech transcripts for robust high-level spoken document analysis
High-level spoken document analysis is required in many applications seeking access to the semantic content of audio data, such as information retrieval, machine translation or au...
Julien Fayolle, Fabienne Moreau, Christian Raymond...
ANLP
2000
157views more  ANLP 2000»
14 years 11 months ago
Experiments on Sentence Boundary Detection
This paper explores the problem of identifying sentence boundaries in the transcriptions produced by automatic speech recognition systems. An experiment which determines the level...
Mark Stevenson, Robert J. Gaizauskas
78
Voted
CEC
2005
IEEE
15 years 3 months ago
Evolutionary algorithm for noun phrase detection in natural language processing
Noun phrases of a document usually are the main information bearers. Thus, the detection of these units is crucial in many applications related to information retrieval, such as co...
Jose Ignacio Serrano, Lourdes Araujo