企業與客戶之間的關係除了商品購買之外，售後服務與客戶需求成為企業掌握客戶與保持良好關係的重要基礎，暢通的溝通管道成為資訊科技時代，企業積極發展的需求之一。伴隨著人工智慧科技的發展與深度學習演算法的出現，讓自然語言處理技術更近一步發展，透過機器的自主學習能力強化機器對語意理解的能力，讓機器人更加擬人化、可處理更複雜之問題。雖然國內在聊天機器人已有許多應用，但在零售業使用聊天機器人的還是非常稀少。
而本論文使用RASA機器學習框架，建置名為智能客服小J的聊天機器人，並應用於零售業電腦硬體設備之售後服務。利用自然語言處理技術Jieba、TF-IDF等工具，進行斷詞處理、關鍵字擷取與詞向量的訓練，建構出零售業領域的語言模型，最終透過RASA NLU模組與RASA Core模組呈現智能客服小J系統。
最後以易用性測試進行系統實驗與半結構性訪談，並以系統易用性量表（SUS）、聊天機器人易用性調查問卷（CUQ）、使用者經驗調查問卷（UEQ）三個指標評估智能客服小J。實驗結果，智能客服小J在SUS、CUQ與UEQ的得分都很好，並受到具有零售背景使用者之認可，表示聊天機器人技術應用於零售業智能客服之可行性極高。

Purchase of goods, after-sales services, and customer need integration are critical building blocks for good customer-enterprise relationships. In the current era dominated by information technology, active development is crucial in enterprises in order to establish a smooth communication channel with the customers. The emergence of artificial intelligence and deep learning algorithms has greatly improve natural language processing, which subsequently allows robots to be more anthropomorphic and capable of handling complex problems. In line with this, although there are many applications of chatbots in Taiwan, the use of chatbot in the retail industry is still rare.
In this thesis, we used the RASA© (Rasa Technologies, Inc., 2021) Conversational AI framework to build a chatbot, named Assistant-J, for the after-sales service of computer hardware devices in the retail industry. We used various natural language processing techniques, including Jieba, TF-IDF, Word2Vec, and Bert to construct a language model for the retail industry training processes. The intelligent customer service system Assistant-J was built through the RASA NLU module and RASA Core module.
We used the System Usability Scale (SUS), Chatbot Usability Questionnaire (CUQ), and User Experience Questionnaire (UEQ) metrics to evaluate Assistant-J. Results of the evaluation showed that Assistant-J satisfaction scores are high and has high acceptability from users with retail background. These results demonstrate the feasibility of applying chatbot technology to intelligent customer service in the retail industry.

論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
目錄 v
圖次 vii
表次 viii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 3
第三節 章節安排 3
第二章 文獻探討 4
第一節 聊天機器人 4
第二節 聊天機器人在零售業中的應用 6
第三節 聊天機器人的易用性設計 8
第三章 研究方法 12
第一節 研究架構 12
第二節 資料集 13
第三節 意圖與實體設計 14
第四節 自然語言處理 15
第五節 資料格式 18
第四章 系統架構與設計 20
第一節 系統架構 20
第二節 系統設計 27
第三節 系統呈現 29
第四節 小結 32
第五章 系統實驗 33
第一節 聊天機器人評估 33
第二節 實驗結果與分析 34
第六章 結論與未來展望 45
第七章 參考文獻 46

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