Abstract
Techniques of automatic extraction of related words are of great importance in many applications such as query expansion and automatic thesaurus construction. In this paper, a method of extracting related words is proposed basing on the statistical information about the co-occurrences of words from huge corpora. The mutual information is one of such statistical measures and has been used for application mainly in natural language processing. A drawback is, however, the mutual information depends mainly on frequencies of words. To overcome this difficulty, we propose as a new measure a normalize deviation of mutual information. We also reveal a correspondence between word ambiguity and related words using word relation graphs constructed using this measure.
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Sugimachi, T., Ishino, A., Takeda, M., Matsuo, F. (2003). A Method of Extracting Related Words Using Standardized Mutual Information. In: Grieser, G., Tanaka, Y., Yamamoto, A. (eds) Discovery Science. DS 2003. Lecture Notes in Computer Science(), vol 2843. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39644-4_49
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DOI: https://doi.org/10.1007/978-3-540-39644-4_49
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