Extracting Condition-Opinion Relations Toward Fine-grained Opinion Mining

A fundamental issue in opinion mining is to search a corpus for opinion units, each of which typically comprises the evalua-tion by an author for a target object from an aspect, such as “This hotel is in a good location”. However, few attempts have been made to address cases where the validity of an evaluation is restricted on a condition in the source text, such as “for traveling with small kids”. In this paper, we propose a method to ex-tract condition-opinion relations from on-line reviews, which enables fine-grained analysis for the utility of target objects de-pending the user attribute, purpose, and situation. Our method uses supervised machine learning to identify sequences of words or phrases that comprise conditions for opinions. We propose several features associated with lexical and syntactic infor-mation, and show their effectiveness ex-perimentally.