Japanese Language Analaysis for Syntactic Tree Mining to Extract Characteristic Contents

Yohsuke Sakao, Takahiro Ikeda, Kenji Satoh, Susumu Akamine


Abstract
Existing syntactic ordered tree mining methods for extracting characteristic contents from text sets have two problems: 1) subtrees which are semantically the same but are different ordered trees fail to be considered equivalent, and 2) raw extracted subtrees can be difficult to understand. In order to avoid these problems, we have developed a method of transforming all ordered trees so that the ordered trees having the same meaning are considered equivalent. We have also developed a method of constructing Japanese texts from extracted subtrees, and evaluated the effectiveness of our methods as applied to syntactic tree mining.
Anthology ID:
2005.mtsummit-posters.3
Volume:
Proceedings of Machine Translation Summit X: Posters
Month:
September 13-15
Year:
2005
Address:
Phuket, Thailand
Venue:
MTSummit
SIG:
Publisher:
Note:
Pages:
339–345
Language:
URL:
https://aclanthology.org/2005.mtsummit-posters.3
DOI:
Bibkey:
Cite (ACL):
Yohsuke Sakao, Takahiro Ikeda, Kenji Satoh, and Susumu Akamine. 2005. Japanese Language Analaysis for Syntactic Tree Mining to Extract Characteristic Contents. In Proceedings of Machine Translation Summit X: Posters, pages 339–345, Phuket, Thailand.
Cite (Informal):
Japanese Language Analaysis for Syntactic Tree Mining to Extract Characteristic Contents (Sakao et al., MTSummit 2005)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2005.mtsummit-posters.3.pdf