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Creating Japanese Political Corpus from Local Assembly Minutes of 47 prefectures.

, , , , , , , and . ALR@COLING, page 78-85. The COLING 2016 Organizing Committee, (2016)

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Detecting Cyberbullying Entries on Informal School Websites Based on Category Relevance Maximization., , , , , and . IJCNLP, page 579-586. Asian Federation of Natural Language Processing / ACL, (2013)Automatic Extraction of Harmful Sentence Patterns with Application in Cyberbullying Detection., , , , and . LTC, volume 10930 of Lecture Notes in Computer Science, page 349-362. Springer, (2015)Using Time Periods Comparison for Eliminating Chronological Discrepancies between Question and Answer Candidates at QALab NTCIR11 Task., , , , , , , , , and 1 other author(s). NTCIR, National Institute of Informatics (NII), (2014)Brute Force Works Best Against Bullying., , , , and . CPCR+ITWP@IJCAI, volume 1440 of CEUR Workshop Proceedings, CEUR-WS.org, (2015)Brute - Force Sentence Pattern Extortion from Harmful Messages for Cyberbullying Detection., , , , , , , and . J. AIS, 20 (8): 4 (2019)Query Expansion for Contextual Question Using Genetic Algorithms., and . AIRS, volume 4182 of Lecture Notes in Computer Science, page 574-580. Springer, (2006)Toward Automatic Support For Japanese Lay Judge System - Processing Precedent Factors For Sentencing Trends Discovery., , , , , and . NTCIR, National Institute of Informatics (NII), (2008)Creating Japanese Political Corpus from Local Assembly Minutes of 47 prefectures., , , , , , , and . ALR@COLING, page 78-85. The COLING 2016 Organizing Committee, (2016)Evaluation of Japanese Dialogue Processing Method Based on Similarity Measure Using tf· AoI., , and . CICLing, volume 2945 of Lecture Notes in Computer Science, page 371-382. Springer, (2004)Sustainable cyberbullying detection with category-maximized relevance of harmful phrases and double-filtered automatic optimization., , , , , , and . Int. J. Child Comput. Interact., (2016)