A SVM Applied Text Categorization of Academia-Industry Collaborative Research and Development Documents on the Web

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.