Opinion Target Network: A Two-Layer Directed Graph for Opinion Target Extraction

Abstract

Unknown opinion targets lead to a low coverage in opinion mining. To deal with this, the previous opinion target extraction methods consider human-compiled opinion targets as seeds and adopt syntactic/statistic patterns to extract new opinion targets. Three problems are notable. 1) Manually compiled opinion targets are too large to be sound seeds. 2) Array that maintains seeds is less effective to represent relations between seeds. 3) Opinion target extraction can hardly achieve a satisfactory performance in merely one cycle. The opinion target network (OTN) is proposed in this paper to organize atom opinion targets of component and attribute in a two-layer directed graph. With multiple cycles of OTN construction, a higher coverage of opinion target extraction is achieved via generalization and propagation. Experiments on Chinese opinion target extraction show that the OTN is promising in handling the unknown opinion targets.