有鑒於近年來行動裝置的發展，使通訊軟體的使用率逐漸提升。聊天機器人也帶動了對話式商務的熱潮。過去有不少以任務導向的聊天機器人為顧客服務，而這些聊天機器人大多是屬於樣板式模型的架構，使用者只能詢問特定的問題，系統從資料庫抓取答案回覆給使用者，使用者得到的回應都是制式化的回答，且因架構缺少靈活度，使用者常會有得不到聊天機器人回應的結果。檢索式模型雖能在資料庫找到較適合答案輸出給使用者，但因答案也需事先存於資料庫中，透過相似度計算來尋找關鍵字進行配對，無法針對上下文進行分析，因此結果也可能導致答案配對不理想。
本研究將對聊天機器人的技術進行探討，以古物領域聊天機器人為主，建置以基於生成式模型的聊天機器人，使聊天機器人能針對整句話的上下文進行分析自動生成回覆解決此問題，解決聊天機器人無法滿足特定族群需求的問題。運用第三方對話資料集與本文所建立的古物領域資料集，將這些資料進行自然語言處理，文本轉換成向量進行模型訓練，透過模型評估指標證明生成式模型分數較檢索式模型高。本研究設計之聊天機器人流程能確保使用者在詢問古物領域專業問題時，得到最相關的回覆。

In recent years, the development of mobile devices has gradually increased the use of communication software. Chatbots have also driven the development of conversational commerce. In the past, there were a lot of task-oriented chatbots doing customer service. Most of these chatbots belong to the rule-based model. Users can only ask some specific questions, so the system will match the answer which were already created in databased, and then reply to the user. The response that the user received is all standardized answer. Also, because of the system architecture lacks flexibility, users often fail to get their response from the chatbot. Although the retrieval model can find a more suitable answer in the database, but the answer also needs to be stored in the database in advance, through similarity calculation to find keywords to match, it is impossible to analyze the context, so the answer matching is not ideal.
This thesis will discuss the technology of chatbots, mainly in the field of antiquities. Build a chatbot based on a generative model, so that the chatbot can analyze the context of the whole sentence and automatically generate a reply to solve this problem. Using the third-party dialogue dataset and the antiquities field dataset created in this article. These data are processed in natural language, and the text is converted into vectors for model training. The model evaluation proves that the score of generative model is higher than retrieval model. The chatbot process designed in this paper can ensure that users get the most relevant answers when they ask professional questions in the field of antiquities.

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