Conversations Based on Search Engine Result Pages

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.

Based on joint work with Zhumin Chen, Jun Ma, Chuan Meng, Christof Monz, Pengjie Ren, Svitlana Vakulenko, and Nikos Voskarides.

[Talk slides]

Speaker Bios

Maarten de Rijke is a University Professor of Artificial Intelligence and Information Retrieval at the University of Amsterdam and Director of the Information and Language Processing Systems lab. De Rijke’s research strives to build ever more intelligent technology to connect people to information. His team pushes the frontiers of search engines, recommender systems, and conversational assistants. They also investigate the influence of the technology they develop on society. De Rijke is the director of the National Innovation Center for Artificial Intelligence.

Séries:
MSR AI Distinguished Lectures and Fireside Chats
Date:
Haut-parleurs:
Maarten de Rijke
Affiliation:
University of Amsterdam

Taille: MSR AI Distinguished Lectures and Fireside Chats