Extraction of cause information from newspaper articles concerning business performance

Hiroyuki Sakai, Shigeru Masuyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We propose a method of extracting cause information from Japanese newspaper articles concerning business performance. Cause information is useful for investors in selecting companies to invest. Our method extracts cause information as a form of causal expression by using statistical information and initial clue phrases automatically. Our method can extract causal expressions without predetermined patterns or complex rules given by hand, and is expected to be applied to other tasks or language for acquiring phrases that have a particular meaning not limited to cause information. We compared our method with our previous method originally proposed for extracting phrases concerning traffic accident causes and experimental results showed that our new method outperforms our previous one.

Original languageEnglish
Title of host publicationArtificial Intelligence and Innovations 2007
Subtitle of host publicationfrom Theory to Applications: Proceedings of the 4th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2007)
EditorsChristos Boukis, Aristodemos Pnevmatikakis, Lazaros Polymenakos
Pages205-212
Number of pages8
DOIs
Publication statusPublished - 26 Nov 2007

Publication series

NameIFIP International Federation for Information Processing
Volume247
ISSN (Print)1571-5736

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Sakai, H., & Masuyama, S. (2007). Extraction of cause information from newspaper articles concerning business performance. In C. Boukis, A. Pnevmatikakis, & L. Polymenakos (Eds.), Artificial Intelligence and Innovations 2007: from Theory to Applications: Proceedings of the 4th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2007) (pp. 205-212). (IFIP International Federation for Information Processing; Vol. 247). https://doi.org/10.1007/978-0-387-74161-1_22