Add to ORKG• Peak inside the black box of Vector Space Models of lexical semantics • through an interactive visualization of word uses • Allow Computational Linguists to do a direct, intrinsic evaluation of their models and the semantics they capture • Provide Lexicologists and Lexicographers with an explorative tool for analyzing word meaning in large corpor
Vector-based semantic analysis is the practice of representing word meanings as semantic vectors, ca...
Vector space word representations are learned from distributional information of words in large corp...
Vector space models (VSMs) represent word meanings as points in a high dimen-sional space. VSMs are ...
Word space models, in the sense of vector space models built on distributional data taken from texts...
In statistical NLP, Semantic Vector Spaces (SVS) are the standard technique for the automatic modeli...
Computers understand very little of the meaning of human language. This profoundly limits our abilit...
Word Space Models (WSMs) are a statistical-computational technique to compare the collocational beha...
Symbolic approaches have dominated NLP as a means to model syntactic and semantic aspects of natural...
The word-space model is a computational model of word meaning that utilizes the distributional patte...
University of Minnesota Ph.D. dissertation. June 2010. Major: Computer Science. Advisor: William Edw...
Semantic Vector Space Model (SVSM) is a powerful tool that helps in the field of Word Sense Inductio...
Investigating the different uses of a word in texts and corpora is a research activity in several fi...
Conceptual space can be carved up linguistically in different ways. The mapping between a set of rel...
Distributed vector space models have recently shown success at capturing the semantic meanings of wo...
Conceptual space can be carved up linguistically in different ways. The mapping between a set of rel...
Vector-based semantic analysis is the practice of representing word meanings as semantic vectors, ca...
Vector space word representations are learned from distributional information of words in large corp...
Vector space models (VSMs) represent word meanings as points in a high dimen-sional space. VSMs are ...
Word space models, in the sense of vector space models built on distributional data taken from texts...
In statistical NLP, Semantic Vector Spaces (SVS) are the standard technique for the automatic modeli...
Computers understand very little of the meaning of human language. This profoundly limits our abilit...
Word Space Models (WSMs) are a statistical-computational technique to compare the collocational beha...
Symbolic approaches have dominated NLP as a means to model syntactic and semantic aspects of natural...
The word-space model is a computational model of word meaning that utilizes the distributional patte...
University of Minnesota Ph.D. dissertation. June 2010. Major: Computer Science. Advisor: William Edw...
Semantic Vector Space Model (SVSM) is a powerful tool that helps in the field of Word Sense Inductio...
Investigating the different uses of a word in texts and corpora is a research activity in several fi...
Conceptual space can be carved up linguistically in different ways. The mapping between a set of rel...
Distributed vector space models have recently shown success at capturing the semantic meanings of wo...
Conceptual space can be carved up linguistically in different ways. The mapping between a set of rel...
Vector-based semantic analysis is the practice of representing word meanings as semantic vectors, ca...
Vector space word representations are learned from distributional information of words in large corp...
Vector space models (VSMs) represent word meanings as points in a high dimen-sional space. VSMs are ...