Document (#38705)

Author

Lund, K.
Burgess, C.

Title

Producing high-dimensional semantic spaces from lexical co-occurrence

Source

Behavior research methods, instruments & computers 28(1996) no.2, S.203-208

Year

1996

Abstract

A procedure that processes a corpus of text and produces numeric vectors containing information about its meanings for each word is presented. This procedure is applied to a large corpus of natural language text taken from Usenet, and the resulting vectors are examined to determine what information is contained within them. These vectors provide the coordinates in a high-dimensional space in which word relationships can be analyzed. Analyses of both vector similarity and multidimensional scaling demonstrate that there is significant semantic information carried in the vectors. A comparison of vector similarity with human reaction times in a single-word priming experiment is presented. These vectors provide the basis for a representational model of semantic memory, hyperspace analogue to language (HAL).

Theme

Semantisches Umfeld in Indexierung u. Retrieval

Object

Hyperspace Analogue to Language

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5. Liddy, E.D.: ¬An alternative representation for documents and queries (1993) 0.27

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