Improving the performance of features extraction from Chinese customer reviews

Now many customers browse a large number of online reviews to know others' word-of-mouth about products and services prior to making their decisions. Meanwhile customer reviews serve as a feedback mechanism that can help suppliers improve their products and services, gaining competitive advantages. Specifically, product feature extractions from reviews are expected to further investigate the views and attitudes of customers. This study aims at analyzing Chinese customer reviews. Our approach was based on a recently introduced mining approach, which further improving the performance by correcting sequence of words in Chinese. Experiments were conducted using the reviews download from Internet as datasets. Empirical results proved the validity of the proposed method.