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Multi-Document Information Consolidation (Dagstuhl Seminar 19182)

Authors: Ido Daga, Iryna Gurevych, Dan Roth, and Amanda Stent

Published in: Dagstuhl Reports, Volume 9, Issue 4 (2019)


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.

Cite as

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)


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@Article{daga_et_al:DagRep.9.4.124,
  author =	{Daga, Ido and Gurevych, Iryna and Roth, Dan and Stent, Amanda},
  title =	{{Multi-Document Information Consolidation (Dagstuhl Seminar 19182)}},
  pages =	{124--139},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Daga, Ido and Gurevych, Iryna and Roth, Dan and Stent, Amanda},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.9.4.124},
  URN =		{urn:nbn:de:0030-drops-113572},
  doi =		{10.4230/DagRep.9.4.124},
  annote =	{Keywords: Information Consolidation, Multi-Document, NLP}
}
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