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Online customer review is considered as a significant informative resource which is useful for both potential customer and product manufacturers. As a result, it is one of the most challenging tasks to mine customer reviews automatically and to provide users with opinion summary. Product features and opinion word play the most important roles in the customers’ opinions mining. In this paper, we dedicate our work to opinion word mining. We proposed an approach for opinion word identification based on the association rule mining algorithm. The method makes full use of co-occurrence syntactic characteristic between product features and opinion word. Firstly, the product feature is identified by two-stage filtering scheme, and secondly the opinion word is extracted through association rule mining. The final experiment results show that the proposed method could not only obtain the product features related to domain characteristics, but identify the opinion word effectively. Meanwhile, our approach possesses much higher precision and recall than Hu’s work.