NITMZ-JU at IJCNLP-2017 Task 4: Customer Feedback Analysis
Somnath Banerjee, Partha Pakray, Riyanka Manna, Dipankar Das, Alexander Gelbukh
Abstract
In this paper, we describe a deep learning framework for analyzing the customer feedback as part of our participation in the shared task on Customer Feedback Analysis at the 8th International Joint Conference on Natural Language Processing (IJCNLP 2017). A Convolutional Neural Network (CNN) based deep neural network model was employed for the customer feedback task. The proposed system was evaluated on two languages, namely, English and French.- Anthology ID:
- I17-4030
- Volume:
- Proceedings of the IJCNLP 2017, Shared Tasks
- Month:
- December
- Year:
- 2017
- Address:
- Taipei, Taiwan
- Editors:
- Chao-Hong Liu, Preslav Nakov, Nianwen Xue
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Asian Federation of Natural Language Processing
- Note:
- Pages:
- 180–183
- Language:
- URL:
- https://aclanthology.org/I17-4030
- DOI:
- Cite (ACL):
- Somnath Banerjee, Partha Pakray, Riyanka Manna, Dipankar Das, and Alexander Gelbukh. 2017. NITMZ-JU at IJCNLP-2017 Task 4: Customer Feedback Analysis. In Proceedings of the IJCNLP 2017, Shared Tasks, pages 180–183, Taipei, Taiwan. Asian Federation of Natural Language Processing.
- Cite (Informal):
- NITMZ-JU at IJCNLP-2017 Task 4: Customer Feedback Analysis (Banerjee et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/I17-4030.pdf