預訓練詞向量模型應用於客服對話系統意圖偵測之研究(Study on Pre-trained Word Vector Model Applied to Intent Detection of Customer Service Dialogue System)
Guan-Yu Chen | Min-Feng Kuo | Tsung-Hsien Yang | Chun-Hsun Chen | I-Bin Liao
Proceedings of the 31st Conference on Computational Linguistics and Speech Processing (ROCLING 2019)
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
Proceedings of the IJCNLP 2017, System Demonstrations
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.
- Chun-Hsun Chen 2
- Jui-Yang Wang 1
- Jen-Chieh Han 1
- Chao-Chuang Shih 1
- Po-Ching Lee 1
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