Abstract
The purpose of this study is to construct a probabilistic hierarchical structure of categories based on a statistical analysis of Japanese corpus data and to verify the validity of the structure by conducting a psychological experiment. At first, the co-occurrence frequencies of adjectives and nouns within modification relations were extracted from a Japanese corpus. Secondly, a probabilistic hierarchical structure was constructed based on the probability, P(category|noun), representing the category membership of the nouns, and utilizing categorization information in a thesaurus and a soft clustering method (Rose’s method ) with co-occurrence frequencies as initial values. This method makes it possible to identify the constructed hierarchical structure. In order to examine the validity of the constructed hierarchy, a psychological experiment was conducted. The results of the experiment verified the psychological validity of the hierarchical structure.
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Terai, A., Liu, B., Nakagawa, M. (2008). Construction of a Probabilistic Hierarchical Structure Based on a Japanese Corpus and a Japanese Thesaurus. In: Tokunaga, T., Ortega, A. (eds) Large-Scale Knowledge Resources. Construction and Application. LKR 2008. Lecture Notes in Computer Science(), vol 4938. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78159-2_13
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DOI: https://doi.org/10.1007/978-3-540-78159-2_13
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