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» Boosting Applied to Word Sense Disambiguation
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COLING
2008
15 years 7 months ago
Word Sense Disambiguation for All Words using Tree-Structured Conditional Random Fields
We propose a supervised word sense disambiguation (WSD) method using tree-structured conditional random fields (TCRFs). By applying TCRFs to a sentence described as a dependency t...
Jun Hatori, Yusuke Miyao, Jun-ichi Tsujii
ACL
2007
15 years 7 months ago
Domain Adaptation with Active Learning for Word Sense Disambiguation
When a word sense disambiguation (WSD) system is trained on one domain but applied to a different domain, a drop in accuracy is frequently observed. This highlights the importance...
Yee Seng Chan, Hwee Tou Ng
ANLP
1997
80views more  ANLP 1997»
15 years 7 months ago
Sequential Model Selection for Word Sense Disambiguation
Statistical models of word-sense disambiguation are often based on a small number of contextual features or on a model that is assumed to characterize the interactions among a set...
Ted Pedersen, Rebecca F. Bruce, Janyce Wiebe
CIKM
2005
Springer
15 years 11 months ago
Word sense disambiguation in queries
This paper presents a new approach to determine the senses of words in queries by using WordNet. In our approach, noun phrases in a query are determined first. For each word in th...
Shuang Liu, Clement T. Yu, Weiyi Meng
EMNLP
2010
15 years 4 months ago
Word Sense Induction Disambiguation Using Hierarchical Random Graphs
Graph-based methods have gained attention in many areas of Natural Language Processing (NLP) including Word Sense Disambiguation (WSD), text summarization, keyword extraction and ...
Ioannis P. Klapaftis, Suresh Manandhar