Abstract
In this work, we explore the combined use of latent semantic analysis (LSA) and multidimensional scaling (MDS) for identifying related concepts and terms. We approach the problem of related term identification by constructing low-dimensional embeddings where related terms are clustered together, and such clusters are spatially arranged according to the semantic relationships among the terms they include. In this work, we demonstrate the proposed methodology for a specific part-of-speech (verbs) of the Spanish language, by using dictionary-based definitions. We also comment on the future use of this experimental framework in the context of other natural language processing tasks such as opinion mining, topic detection and automatic summarization.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bensch, P.A., Saviteh, W.J.: An occurrence-based model of word categorization. Annuals of Mathematics and Artificial Intelligence 14, 1–16 (1995)
Cattell, R.B.: The scree test for the number of factors. Multivariate Behavioral Research 1, 245–276 (1966)
Cox, M.F., Cox, M.A.A.: Multidimensional Scaling. Chapman and Hall, Boca Raton (2001)
Deerwester, S., Dumais, S., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science 41(6), 391–407 (1990)
Evans, D.A., Handerson, S.K., Monarch, I.A., Pereiro, J., Delon, L., Hersh, W.R.: Mapping Vocabularies Using Latent Semantics. In: Grefenstette, G. (ed.) Cross-Language Information Retrieval, pp. 63–80. Kluwer Academic Publishers, Dordrecht (1998)
Hofmann, T.: Probabilistic Latent Semantic Analysis. In: Proceedings of Uncertainty in Artificial Intelligence, UAI 1999, pp. 289–296 (1999)
van Eck, N., Waltman, L., van den Berg, J.: A novel algorithm for visualizing concept associations. In: Proceedings of the 16th International Workshop on Database and Expert System Applications, pp. 405–409 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Banchs, R.E. (2009). Semantic Mapping for Related Term Identification. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2009. Lecture Notes in Computer Science, vol 5449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00382-0_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-00382-0_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00381-3
Online ISBN: 978-3-642-00382-0
eBook Packages: Computer ScienceComputer Science (R0)