Mining rules for rewriting states in a transition-based dependency parser

Authors:
Akihiro Inokuchi;Ayumu Yamaoka;Takashi Washio;Yuji Matsumoto;Masayuki Asahara;Masakazu Iwatate;Hideto Kazawa
Affiliations:
Institute of Scientific and Industrial Research, Osaka University, Japan;Institute of Scientific and Industrial Research, Osaka University, Japan;Institute of Scientific and Industrial Research, Osaka University, Japan;Nara Institute of Science and Technology, Japan;National Institute for Japanese Language and Linguistics, Japan;HDE, Inc., Japan;Google, Inc., Japan
Venue:
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Year:
2012

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Abstract

Methods for mining graph sequences have recently attracted considerable interest from researchers in the data-mining field. A graph sequence is one of the data structures that represent changing networks. The objective of graph sequence mining is to enumerate common changing patterns appearing more frequently than a given threshold from graph sequences. Syntactic dependency analysis has been recognized as a basic process in natural language processing. In a transition-based parser for dependency analysis, a transition sequence can be represented by a graph sequence where each graph, vertex, and edge respectively correspond to a state, word, and dependency. In this paper, we propose a method for mining rules for rewriting states reaching incorrect final states to states reaching the correct final state, and propose a dependency parser that uses rewriting rules. The proposed parser is comparable to conventional dependency parsers in terms of computational complexity.