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Yan, Xin; Li, Xue and Song, Dawei
(2004).
DOI: https://doi.org/10.1007/b104566
Abstract
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.
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- Item ORO ID
- 9324
- 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 or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
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