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.