{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T03:55:15Z","timestamp":1787025315680,"version":"build-2736575974"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>We present a document-grounded matching network (DGMN) for response selection that can power a knowledge-aware retrieval-based chatbot system. The challenges of building such a model lie in how to ground conversation contexts with background documents and how to recognize important information in the documents for matching. To overcome the challenges, DGMN fuses information in a document and a context into representations of each other, and dynamically determines if grounding is necessary and importance of different parts of the document and the context through hierarchical interaction with a response at the matching step. Empirical studies on two public data sets indicate that DGMN can significantly improve upon state-of-the-art methods and at the same time enjoys good interpretability.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/756","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:46:05Z","timestamp":1564285565000},"page":"5443-5449","source":"Crossref","is-referenced-by-count":18,"title":["A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots"],"prefix":"10.24963","author":[{"given":"Xueliang","family":"Zhao","sequence":"first","affiliation":[{"name":"Institute of Computer Science and Technology, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chongyang","family":"Tao","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Technology, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Wu","sequence":"additional","affiliation":[{"name":"Microsoft Corporation, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Can","family":"Xu","sequence":"additional","affiliation":[{"name":"Microsoft Corporation, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongyan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Technology, Peking University, Beijing, China"},{"name":"Center for Data Science, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Yan","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Technology, Peking University, Beijing, China"},{"name":"Center for Data Science, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T03:51:36Z","timestamp":1564285896000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/756"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/756","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}