A Novel Approach of Extracting Opinion Targets and Opinion Words from Online Review

摘要

In opinion mining, the precision of extracting opinion words and opinion targets from online review dataset can severely influence the precision of opinion mining systems. In this paper, we propose a graph-based filtering approach to extract effective opinion targets and opinion words from the candidate words, which can be mined by word-based translation model in a monolingual scenario. Experimental results on four real Chinese review datasets show that our approach is promising performance.