Abstract
Increasing interest is recently observed in the method of extracting human opinions from a large scale of heterogeneous text data such as Web documents.To automate the process of opinion extraction, having a collection of evaluative expressions such as “the seats are comfortable” would be useful.However, it can be prohibitively costly to manually create an exhaustive list of such expressions for many domains, because they tend to be domain-dependent.Motivated by this background, we have been exploring the way to accelerate the process of collecting evaluative expressions by applying a text mining technique.This paper proposes a semi-automatic method that uses particular cooccurrence patterns of evaluated subjects, focused attributes and values.Experimental results show its efficiency compared to manual collection of those expressions.
