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Positioning for conceptual development using latent semantic analysis

Wild, Fridolin; Hoisl, Bernhard and Burek, Gaston (2009). Positioning for conceptual development using latent semantic analysis. In: The 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2009), Workshop on GEMS: GEometical Models of Natural Language Semantics, 31 Mar 2009, Athens, Greece.

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With increasing opportunities to learn online, the problem of positioning learners in an educational network of content offers new possibilities for the utilisation of geometry-based natural language processing techniques.

In this article, the adoption of latent semantic analysis (LSA) for guiding learners in their conceptual development is investigated. We propose five new algorithmic derivations of LSA and test their validity for positioning in an experiment in order to draw back conclusions on the suitability of machine learning from previously accredited evidence. Special attention is thereby directed towards the role of distractors and the calculation of thresholds when using similarities as a proxy for assessing conceptual closeness.

Results indicate that learning improves positioning. Distractors are of low value and seem to be replaceable by generic noise to improve threshold calculation. Furthermore, new ways to flexibly calculate thresholds could be identified.

Item Type: Conference or Workshop Item
Copyright Holders: 2009 Association for Computational Linguistics
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 25230
Depositing User: Kay Dave
Date Deposited: 08 Dec 2010 12:41
Last Modified: 08 Dec 2018 20:09
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