Abstract
When acquiring synonyms from large corpora, it is important to deal not only with such surface information as the context of the words but also their latent semantics. This paper describes how to utilize a latent semantic model PLSI to acquire synonyms automatically from large corpora. PLSI has been shown to achieve a better performance than conventional methods such as tf·idf and LSI, making it applicable to automatic thesaurus construction. Also, various PLSI techniques have been shown to be effective including: (1) use of Skew Divergence as a distance/similarity measure; (2) removal of words with low frequencies, and (3) multiple executions of PLSI and integration of the results.
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Hagiwara, M., Ogawa, Y., Toyama, K. (2005). PLSI Utilization for Automatic Thesaurus Construction. In: Dale, R., Wong, KF., Su, J., Kwong, O.Y. (eds) Natural Language Processing – IJCNLP 2005. IJCNLP 2005. Lecture Notes in Computer Science(), vol 3651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562214_30
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DOI: https://doi.org/10.1007/11562214_30
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