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ACL
2004
13 years 9 months ago
Finding Predominant Word Senses in Untagged Text
In word sense disambiguation (WSD), the heuristic of choosing the most common sense is extremely powerful because the distribution of the senses of a word is often skewed. The pro...
Diana McCarthy, Rob Koeling, Julie Weeds, John A. ...
ACL
2006
13 years 9 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone
ACL
2006
13 years 9 months ago
Modeling Human Sentence Processing Data with a Statistical Parts-of-Speech Tagger
It has previously been assumed in the psycholinguistic literature that finite-state models of language are crucially limited in their explanatory power by the locality of the prob...
Jihyun Park
ACL
2006
13 years 9 months ago
A Finite-State Model of Human Sentence Processing
It has previously been assumed in the psycholinguistic literature that finite-state models of language are crucially limited in their explanatory power by the locality of the prob...
Jihyun Park, Chris Brew
APBC
2004
166views Bioinformatics» more  APBC 2004»
13 years 9 months ago
THEMATICS is Effective for Active Site Prediction in Comparative Model Structures
THEMATICS (Theoretical Microscopic Titration Curves) is a simple, reliable computational predictor of the active sites of enzymes from structure. Our method, based on well-establi...
Ihsan A. Shehadi, Alper Uzun, Leonel F. Murga, Val...