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A correlation analysis on LSA and HAL semantic space models

Yan, Xin; Li, Xue and Song, Dawei (2004). A correlation analysis on LSA and HAL semantic space models. In: ed. Computational and Information Science. Lecture Notes in Computer Science, Volume 331. Berlin: Springer, pp. 711–717.

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In this paper, we compare a well-known semantic spacemodel, Latent Semantic Analysis (LSA) with another model, Hyperspace Analogue to Language (HAL) which is widely used in different area, especially in automatic query refinement. We conduct this comparative analysis to prove our hypothesis that with respect to ability of extracting the lexical information from a corpus of text, LSA is quite similar to HAL. We regard HAL and LSA as black boxes. Through a Pearsons correlation analysis to the outputs of these two black boxes, we conclude that LSA highly co-relates with HAL and thus there is a justification that LSA and HAL can potentially play a similar role in the area of facilitating automatic query refinement. This paper evaluates LSA in a new application area and contributes an effective way to compare different semantic space models.

Item Type: Book Section
ISBN: 3-540-24127-2, 978-3-540-24127-0
Keywords: Correlation analysis; hyperspace analogue to language; latent semantic indexing; automatic query refinement
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 9324
Depositing User: Users 6898 not found.
Date Deposited: 28 Sep 2007
Last Modified: 07 Dec 2018 09:07
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