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» Automatically Discovering Word Senses
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NLDB
2005
Springer
14 years 1 months ago
On Some Optimization Heuristics for Lesk-Like WSD Algorithms
For most English words, dictionaries give various senses: e.g., “bank” can stand for a financial institution, shore, set, etc. Automatic selection of the sense intended in a gi...
Alexander F. Gelbukh, Grigori Sidorov, Sang-Yong H...
ECIR
2008
Springer
13 years 9 months ago
Filaments of Meaning in Word Space
Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dim...
Jussi Karlgren, Anders Holst, Magnus Sahlgren
SDM
2009
SIAM
105views Data Mining» more  SDM 2009»
14 years 4 months ago
Exploiting Semantic Constraints for Estimating Supersenses with CRFs.
The annotation of words and phrases by ontology concepts is extremely helpful for semantic interpretation. However many ontologies, e.g. WordNet, are too fine-grained and even hu...
Gerhard Paaß, Frank Reichartz
CSL
2004
Springer
13 years 7 months ago
HyperLex: lexical cartography for information retrieval
This article describes an algorithm called HyperLex that is capable of automatically determining word uses in a textbase without recourse to a dictionary. The algorithm makes use ...
Jean Véronis
AAAI
2010
13 years 9 months ago
What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model
In this paper, we propose a generative model to automatically discover the hidden associations between topics words and opinion words. By applying those discovered hidden associat...
Bi Chen, Leilei Zhu, Daniel Kifer, Dongwon Lee