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» Discovering Word Meanings Based on Frequent Termsets
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ECML
2007
Springer
13 years 9 months ago
Discovering Word Meanings Based on Frequent Termsets
Word meaning ambiguity has always been an important problem in information retrieval and extraction, as well as, text mining (documents clustering and classification). Knowledge di...
Henryk Rybinski, Marzena Kryszkiewicz, Grzegorz Pr...
ICDM
2008
IEEE
127views Data Mining» more  ICDM 2008»
13 years 10 months ago
Word Sense Discovery for Web Information Retrieval
Word meaning disambiguation has always been an important problem in many computer science tasks, such as information retrieval and extraction. One of the problems, faced in automa...
Tomasz Nykiel, Henryk Rybinski
AAAI
2004
13 years 5 months ago
Discriminating Among Word Meanings by Identifying Similar Contexts
Word sense discrimination is an unsupervised clustering problem, which seeks to discover which instances of a word/s are used in the same meaning. This is done strictly based on i...
Amruta Purandare, Ted Pedersen
CICLING
2007
Springer
13 years 9 months ago
Text Categorization for Improved Priors of Word Meaning
Distributions of the senses of words are often highly skewed. This fact is exploited by word sense disambiguation (WSD) systems which back off to the predominant (most frequent) s...
Rob Koeling, Diana McCarthy, John Carroll
ECIR
2008
Springer
13 years 5 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