Analyzing the Effect of Domain Adaptation for Dependency Parsers by Clustering Parsing Errors

Abstract

This paper reports on an analysis of the effect of additional training of Japanese dependency parsers across multiple domains from a bird’s-eye view. Parsing errors were collected before and after additional training using target domain data. We conducted cluster analysis of the parsing errors represented as dense real vectors, which were obtained from the internal states of the parser. Through quantitative and qualitative analysis of the clusters, the types and numbers of the parsing errors across multiple target domains were investigated. Several hypotheses concerning the effect of additional training were developed on the basis of the cluster analysis and verified through statistical analysis of the corpus. The results suggest that the main effect of additional training was learning the difference in the distributions of the correct syntactic structures for similar word sequences in different domains.