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ACL
1998
15 years 7 months ago
Trainable, Scalable Summarization Using Robust NLP and Machine Learning
We describe a trainable and scalable summarization system which utilizes features derived from information retrieval, information extraction, and NLP techniques and on-line resour...
Chinatsu Aone, Mary Ellen Okurowski, James Gorlins...
AAAI
1994
15 years 7 months ago
Inducing Deterministic Prolog Parsers from Treebanks: A Machine Learning Approach
or untagged treebanks. ' When trained on an untagged This paper presents a method for constructing deterministic Prolog parsers from corpora of parsed sentences. Our approach ...
John M. Zelle, Raymond J. Mooney
LREC
2008
104views Education» more  LREC 2008»
15 years 8 months ago
Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a ...
Lukasz Degórski, Michal Marcinczuk, Adam Pr...
NIPS
2004
15 years 7 months ago
A Machine Learning Approach to Conjoint Analysis
Choice-based conjoint analysis builds models of consumer preferences over products with answers gathered in questionnaires. Our main goal is to bring tools from the machine learni...
Olivier Chapelle, Zaïd Harchaoui
AAAI
1998
15 years 7 months ago
Machine Learning of Generic and User-Focused Summarization
A key problem in text summarization is finding a salience function which determines what information in the source should be included in the summary. This paper describes the use ...
Inderjeet Mani, Eric Bloedorn