{"id":629865,"date":"2019-12-03T00:00:07","date_gmt":"2019-12-03T08:00:07","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=629865"},"modified":"2020-01-07T12:49:30","modified_gmt":"2020-01-07T20:49:30","slug":"conversations-based-on-search-engine-result-pages","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/conversations-based-on-search-engine-result-pages\/","title":{"rendered":"Conversations Based on Search Engine Result Pages"},"content":{"rendered":"
How might we convey the information that is traditionally returned by a search engine in the form of a complex search engine result page (SERP) in a meaningful and natural conversation? In the talk, Maarten starts from recent work on so-called background based conversations, where a conversational agent has access to additional background information to help it generate more natural and appropriate responses. Then, he talks about ongoing work on our next step: SERP-based conversations. He explains the task definitions, describes pipelines (subtasks), baselines, datasets, etc. Finally, Maarten describes the differences between background-based and SERP-based conversations and their relations to other, related tasks. Work on SERP-based conversations is in its early stages, leaving lots of opportunities for follow-up research.<\/p>\n
Based on joint work with Zhumin Chen, Jun Ma, Chuan Meng, Christof Monz, Pengjie Ren, Svitlana Vakulenko, and Nikos Voskarides.<\/p>\n