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» Question Answering Using a Large NLP System
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121
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ACL
2010
15 years 20 days ago
Unsupervised Ontology Induction from Text
Extracting knowledge from unstructured text is a long-standing goal of NLP. Although learning approaches to many of its subtasks have been developed (e.g., parsing, taxonomy induc...
Hoifung Poon, Pedro Domingos
121
Voted
CJ
2002
67views more  CJ 2002»
15 years 2 months ago
Using Bloom Filters to Speed-up Name Lookup in Distributed Systems
Bloom filters make use of a "probabilistic" hash-coding method to reduce the amount of space required to store a hash set. A Bloom filter offers a trade-off between its ...
Mark C. Little, Santosh K. Shrivastava, Neil A. Sp...
102
Voted
COLING
2010
14 years 9 months ago
Exploring variation across biomedical subdomains
Previous research has demonstrated the importance of handling differences between domains such as "newswire" and "biomedicine" when porting NLP systems from on...
Tom Lippincott, Diarmuid Ó Séaghdha,...
122
Voted
COLING
2010
14 years 9 months ago
Automatic Temporal Expression Normalization with Reference Time Dynamic-Choosing
Temporal expressions in texts contain significant temporal information. Understanding temporal information is very useful in many NLP applications, such as information extraction,...
Xujian Zhao, Peiquan Jin, Lihua Yue
128
Voted
ACL
2006
15 years 4 months ago
Improving QA Accuracy by Question Inversion
This paper demonstrates a conceptually simple but effective method of increasing the accuracy of QA systems on factoid-style questions. We define the notion of an inverted questio...
John M. Prager, Pablo Ariel Duboué, Jennife...