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» Automatically Discovering Word Senses
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TSD
2001
Springer
14 years 3 days ago
Method for WordNet Enrichment Using WSD
This paper presents a new method to enrich semantically WordNet with categories from general domain classification systems. The method is performed in two consecutive steps. First,...
Andrés Montoyo, Manuel Palomar, German Riga...
ACL
2003
13 years 9 months ago
Syntactic Features and Word Similarity for Supervised Metonymy Resolution
We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Malvina Nissim, Katja Markert
AVSS
2006
IEEE
14 years 1 months ago
Learning Foveal Sensing Strategies in Unconstrained Surveillance Environments
In this paper we report on techniques for automatically learning foveal sensing strategies for an active pan-tiltzoom camera. The approach uses reinforcement learning to discover ...
Andrew D. Bagdanov, Alberto Del Bimbo, Walter Nunz...
KCAP
2009
ACM
14 years 2 months ago
Overview of a semantic disambiguation method for unstructured web contexts
In this paper we give an overview of a multiontology disambiguation method, targeted to discover the intended meaning of words in unstructured web contexts. It receives an ambiguo...
Jorge Gracia, Eduardo Mena
KDD
2007
ACM
206views Data Mining» more  KDD 2007»
14 years 8 months ago
Automatic labeling of multinomial topic models
Multinomial distributions over words are frequently used to model topics in text collections. A common, major challenge in applying all such topic models to any text mining proble...
Qiaozhu Mei, Xuehua Shen, ChengXiang Zhai