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

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.