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» Cost-Sensitive Learning in Answer Extraction
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AI
2005
Springer
14 years 11 months ago
Learning to talk about events from narrated video in a construction grammar framework
The current research presents a system that learns to understand object names, spatial relation terms and event descriptions from observing narrated action sequences. The system e...
Peter Ford Dominey, Jean-David Boucher
ACL
2001
15 years 1 months ago
Japanese Named Entity Recognition based on a Simple Rule Generator and Decision Tree Learning
Named entity (NE) recognition is a task in which proper nouns and numerical information in a document are detected and classified into categories such as person, organization, loc...
Hideki Isozaki
DEBU
2000
101views more  DEBU 2000»
14 years 11 months ago
Learning to Understand the Web
In a traditional information retrieval system, it is assumed that queries can be posed about any topic. In reality, a large fraction of web queries are posed about a relatively sm...
William W. Cohen, Andrew McCallum, Dallan Quass
NLPRS
2001
Springer
15 years 4 months ago
Named Entity Recognition using Machine Learning Methods and Pattern-Selection Rules
Named Entity recognition, as a task of providing important semantic information, is a critical first step in Information Extraction and QuestionAnswering system. This paper propos...
Choong-Nyoung Seon, Youngjoong Ko, Jeong-Seok Kim,...
JAIR
2006
137views more  JAIR 2006»
14 years 11 months ago
Learning Sentence-internal Temporal Relations
In this paper we propose a data intensive approach for inferring sentence-internal temporal relations. Temporal inference is relevant for practical NLP applications which either e...
Maria Lapata, Alex Lascarides