A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification
Jui-Yang Wang, Min-Feng Kuo, Jen-Chieh Han, Chao-Chuang Shih, Chun-Hsun Chen, Po-Ching Lee, Richard Tzong-Han Tsai
Abstract
In the paper, we propose an information retrieval based (IR-based) Question Answering (QA) system to assist online customer service staffs respond users in the telecom domain. When user asks a question, the system retrieves a set of relevant answers and ranks them. Moreover, our system uses a novel reranker to enhance the ranking result of information retrieval. It employs the word2vec model to represent the sentences as vectors. It also uses a sub-category feature, predicted by the k-nearest neighbor algorithm. Finally, the system returns the top five candidate answers, making online staffs find answers much more efficiently.- Anthology ID:
- I17-3005
- Volume:
- Proceedings of the IJCNLP 2017, System Demonstrations
- Month:
- November
- Year:
- 2017
- Address:
- Tapei, Taiwan
- Editors:
- Seong-Bae Park, Thepchai Supnithi
- Venue:
- IJCNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 17–20
- Language:
- URL:
- https://aclanthology.org/I17-3005
- DOI:
- Cite (ACL):
- Jui-Yang Wang, Min-Feng Kuo, Jen-Chieh Han, Chao-Chuang Shih, Chun-Hsun Chen, Po-Ching Lee, and Richard Tzong-Han Tsai. 2017. A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification. In Proceedings of the IJCNLP 2017, System Demonstrations, pages 17–20, Tapei, Taiwan. Association for Computational Linguistics.
- Cite (Informal):
- A Telecom-Domain Online Customer Service Assistant Based on Question Answering with Word Embedding and Intent Classification (Wang et al., IJCNLP 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/I17-3005.pdf