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» From Frequency to Meaning: Vector Space Models of Semantics
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ICIP
2005
IEEE
14 years 10 months ago
Learning hidden semantic cues using support vector clustering
This paper presents a method to infer hidden semantic cues by accumulating the knowledge learned from relevance feedback sessions. We propose to explicitly represent a semantic sp...
Jia-Wen Tung, Chiou-Ting Hsu
SMC
2010
IEEE
202views Control Systems» more  SMC 2010»
13 years 6 months ago
Evaluating the performance of nonnegative matrix factorization for constructing semantic spaces: Comparison to latent semantic a
—This study examines the ability of nonnegative matrix factorization (NMF) as a method for constructing semantic spaces, in which the meaning of each word is represented by a hig...
Akira Utsumi
QI
2009
Springer
190views Physics» more  QI 2009»
14 years 3 months ago
Characterizing Pure High-Order Entanglements in Lexical Semantic Spaces via Information Geometry
An emerging topic in Quantuam Interaction is the use of lexical semantic spaces, as Hilbert spaces, to capture the meaning of words. There has been some initial evidence that the p...
Yuexian Hou, Dawei Song
ACL
2008
13 years 10 months ago
Vector-based Models of Semantic Composition
This paper proposes a framework for representing the meaning of phrases and sentences in vector space. Central to our approach is vector composition which we operationalize in ter...
Jeff Mitchell, Mirella Lapata
LREC
2010
163views Education» more  LREC 2010»
13 years 10 months ago
Meaning Representation: From Continuity to Discreteness
This paper presents a geometric approach to meaning representation within the framework of continuous mathematics. Meaning representation is a central issue in Natural Language Pr...
Fabienne Venant