Research talk: Search, summarization, and sensemaking
- Marti Hearst | UC Berkeley
- Microsoft Research Summit 2021 | The Future of Search & Recommendation
Natural language processing (NLP) has undergone head-spinning advances over the last 5–10 years. At the same time, user interfaces for search have remained somewhat static. Has NLP advanced enough to more actively aid searchers in the sensemaking process? In this talk, Professor Marti Hearst of UC Berkeley summarizes some recent work by her lab, some in collaboration with Microsoft Research, on integration of summarization and question answering into news chat interfaces. She will also discuss other recent developments of integrating NLP into scholarly document search and discuss how this might lead to more powerful support for making sense of information within and across search results.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
The Future of Search & Recommendation
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Keynote: Universal search and recommendation
- Paul Bennett
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Research talk: System frontiers for dense retrieval
- Jason Li,
- Knut Risvik
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Research talk: Domain-specific pretraining for vertical search
- Tristan Naumann
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Panel: The future of search and recommendation: Beyond web search
- Eric Horvitz,
- Nitin Agrawal,
- Soumen Chakrabati
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Panel: Causality in search and recommendation systems
- Emre Kiciman,
- Amit Sharma,
- Dean Eckles
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