publication . Conference object . Part of book or chapter of book . 2008

Filaments of Meaning in Word Space

Jussi Karlgren;
Open Access
  • Published: 01 Jan 2008
  • Country: Sweden
Abstract
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 dimensionality of typical vector space models lead to unintuitive effects on modeling likeness of meaning and that the local structure of word spaces is where interesting semantic relations reside. We show that the local structure of word spaces has substantially different dimensionality and character than the global space and that this structure shows potential to be exploited for further semantic analysis using methods for local analysis of vector space structure rather than globally sc...
Subjects
free text keywords: Principal component analysis, Artificial intelligence, business.industry, business, Semantic similarity, Random indexing, Vector space, Latent semantic analysis, Computer science, Curse of dimensionality, Natural language processing, computer.software_genre, computer, Vector space model, Function space
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Digital Humanities and Cultural Heritage
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publication . Conference object . Part of book or chapter of book . 2008

Filaments of Meaning in Word Space

Jussi Karlgren;