Abstract
A method of automatically extracting Japanese documents describing University-Industry (U-I) relations from the Web is proposed. The proposed method consists of Japanese text processing and support vector machine (SVM) classification. The SVM feature selections were customized for U-I relations documents. The strongest experimental result was 79.95 of accuracy and 81.17 of f-measure.
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Kurakawa, K., Sun, Y., Yamashita, N., Baba, Y. (2014). A SVM Applied Text Categorization of Academia-Industry Collaborative Research and Development Documents on the Web. In: Vicari, D., Okada, A., Ragozini, G., Weihs, C. (eds) Analysis and Modeling of Complex Data in Behavioral and Social Sciences. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-06692-9_19
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DOI: https://doi.org/10.1007/978-3-319-06692-9_19
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