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» Mining Causality from Texts for Question Answering System
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DMKD
2000
ACM
110views Data Mining» more  DMKD 2000»
13 years 12 months ago
Combining Strategies for Extracting Relations from Text Collections
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use...
Eugene Agichtein, Eleazar Eskin, Luis Gravano
BMCBI
2008
140views more  BMCBI 2008»
13 years 7 months ago
Corpus annotation for mining biomedical events from literature
Background: Advanced Text Mining (TM) such as semantic enrichment of papers, event or relation extraction, and intelligent Question Answering have increasingly attracted attention...
Jin-Dong Kim, Tomoko Ohta, Jun-ichi Tsujii
FLAIRS
2007
13 years 9 months ago
Indexing Documents by Discourse and Semantic Contents from Automatic Annotations of Texts
The basic aim of the model proposed here is to automatically build semantic metatext structure for texts that would allow us to search and extract discourse and semantic informati...
Brahim Djioua, Jean-Pierre Desclés
TREC
2007
13 years 8 months ago
Lymba's PowerAnswer 4 in TREC 2007
This paper reports on Lymba Corporation’s (a spinoff of Language Computer Corporation) participation in the TREC 2007 Question Answering track. An overview of the PowerAnswer 4 ...
Dan I. Moldovan, Christine Clark, Moldovan Bowden
BMCBI
2007
151views more  BMCBI 2007»
13 years 7 months ago
A comparison study on algorithms of detecting long forms for short forms in biomedical text
Motivation: With more and more research dedicated to literature mining in the biomedical domain, more and more systems are available for people to choose from when building litera...
Manabu Torii, Zhang-Zhi Hu, Min Song, Cathy H. Wu,...