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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Sugimachi, T., Ishino, A., Takeda, M., & Matsuo, F. (2003). A method of extracting related words using standardized mutual information. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2843, 478–485. https://doi.org/10.1007/978-3-540-39644-4_49
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