Shuying Lin


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SentiNLP at IJCNLP-2017 Task 4: Customer Feedback Analysis Using a Bi-LSTM-CNN Model
Shuying Lin | Huosheng Xie | Liang-Chih Yu | K. Robert Lai
Proceedings of the IJCNLP 2017, Shared Tasks

The analysis of customer feedback is useful to provide good customer service. There are a lot of online customer feedback are produced. Manual classification is impractical because the high volume of data. Therefore, the automatic classification of the customer feedback is of importance for the analysis system to identify meanings or intentions that the customer express. The aim of shared Task 4 of IJCNLP 2017 is to classify the customer feedback into six tags categorization. In this paper, we present a system that uses word embeddings to express the feature of the sentence in the corpus and the neural network as the classifier to complete the shared task. And then the ensemble method is used to get final predictive result. The proposed method get ranked first among twelve teams in terms of micro-averaged F1 and second for accura-cy metric.