Min-Feng Kuo


2019

pdf bib
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)

2017

pdf bib
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.