Extraction from the Web of Articles Describing Problems, Their Solutions, and Their Causes

In this study, we extracted articles describing problems, articles describing their solutions, and articles describing their causes from a Japanese Q&A style Web forum using a supervised machine learning with 0.70, 0.86, and 0.56 F values, respectively. We confirmed that these values are signifi...

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Veröffentlicht in:	IEICE Transactions on Information and Systems 2011/03/01, Vol.E94.D(3), pp.734-737
Hauptverfasser:	MURATA, Masaki, TANJI, Hiroki, YAMAMOTO, Kazuhide, SAEGER, Stijn DE, KAKIZAWA, Yasunori, TORISAWA, Kentaro
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences causes Exact sciences and technology Interconnected networks learning Networks and services in france and abroad problems solutions Telecommunications Telecommunications and information theory Teleprocessing networks. Isdn Web
Online-Zugang:	Volltext
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Zusammenfassung:	In this study, we extracted articles describing problems, articles describing their solutions, and articles describing their causes from a Japanese Q&A style Web forum using a supervised machine learning with 0.70, 0.86, and 0.56 F values, respectively. We confirmed that these values are significantly better than their baselines. This extraction will be useful to construct an application that can search for problems provided by users and display causes and potential solutions.
ISSN:	0916-8532 1745-1361
DOI:	10.1587/transinf.E94.D.734