DagRep.9.4.124.pdf
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Multi-Document Information Consolidation (Dagstuhl Seminar 19182)
Authors and all authors of the abstracts in this report
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Dagstuhl Reports, Volume 9, Issue 4
Volume: Dagstuhl Reports, Volume 9
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2019-09-30
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Ido Daga, Iryna Gurevych, Dan Roth, and Amanda Stent. Multi-Document Information Consolidation (Dagstuhl Seminar 19182). In Dagstuhl Reports, Volume 9, Issue 4, pp. 124-139, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/DagRep.9.4.124
https://doi.org/10.4230/DagRep.9.4.124
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19182 "Multi-Document Information Consolidation". At this 5-day Dagstuhl seminar, an interdisciplinary collection of leading researchers discussed and develop research ideas to address multi-documents in machine learning and NLP systems. In particular, the seminar addressed four major topics: 1) how to represent information in multi-document repositories; 2) how to support inference over multi-document repositories; 3) how to summarize and visualize multi-document repositories for decision support; and 4) how to do information validation on multi-document repositories. General talks as well as topic-specific talks were given to stimulate the discussion between the participants, which lead to various new research ideas.
Keywords
- Information Consolidation
- Multi-Document
- NLP
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