Mining Frequent and Infrequent Features from Chinese Customer Reviews
نویسندگان
چکیده
Customer reviews serve as a feedback mechanism that can help suppliers enhance their products and services, then gain competitive advantages. Mining Product features from reviews are expected to further investigate the views and attitudes of customers. This study is focus on one subtask of sentiment analysis. We want to extract the product frequent and infrequent features from Chinese customer reviews. Our approach is based on associated rule technique, and we further propose a algorithm which integrated the selfconstruct features datasets from websites to identify infrequent features. Experiments are conducted by using the reviews which download from Internet as corpus. Results proved that the algorithm will improve the performance of product features extraction, which will be helpful for identifying the real concern of customers.
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