本研究發展幽默語料庫，開發相關的技術，實作一個基於檢索方法的「破冰機器人」系統，讓使用者透過對話找出相關的笑話，在與人互動時打破冰冷的氣氛，活絡陌生、尷尬的情境，最後評估其運用成效。透過資訊系統開發研究法的循環步驟，經過回饋後加入Word2Vec的查詢擴展、關鍵詞查詢提示，以及好笑話的隨機推薦等功能，讓使用者找不到笑話的比例從25.4%降低到16.7%，而系統達到的破冰效果從27.9%提升到39.9%。綜合而言，本研究不僅蒐集編製了近5,000則正體中文幽默語料庫，也建置中文幽默對話應用系統，語料與程式公開於https://github.com/SamTseng/icebreaker。本研究結論提供了實證經驗與意涵：自動化豐富笑話語料並確保其幽默程度，以及提供推薦功能，是提升此類服務成效的重要研發工作。

This research is to construct a humorous corpus, develop related technologies, implement a retrieval-based “icebreaker chatbot” system which allows users to find relevant jokes for use in relaxing an unduly formal atmosphere when interacting with people, and finally evaluate its effectiveness. Through the iterative steps of the information system development research method, query expansion based on Word2Vec technology, frequent keyword prompts, and random recommendation of good jokes are added after user feedback. The results are that the proportion of user queries that fail to find jokes is reduced from 25.4% to 16.7% and that the icebreaking effect achieved has been increased from 27.9% to 39.9%. The importance of this research not only compiled a corpus of nearly 5,000 Chinese jokes, but also built a Chinese humor dialogue system, which have both been publicized at https://github.com/SamTseng/icebreaker for future use and verification. Empirical experience and implications of this study include: automating the richness and quality of joke corpus and providing recommendation service are important R & D efforts to improve the effectiveness of such services.