License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagRep.9.4.124
URN: urn:nbn:de:0030-drops-113572
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Daga, Ido ; Gurevych, Iryna ; Roth, Dan ; Stent, Amanda
Weitere Beteiligte (Hrsg. etc.): Ido Dagan and Iryna Gurevych and Dan Roth and Amanda Stent

Multi-Document Information Consolidation (Dagstuhl Seminar 19182)

dagrep_v009_i004_p124_19182.pdf (7 MB)


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.

BibTeX - Entry

  author =	{Ido Daga and Iryna Gurevych and Dan Roth and Amanda Stent},
  title =	{{Multi-Document Information Consolidation (Dagstuhl Seminar 19182)}},
  pages =	{124--140},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Ido Dagan and Iryna Gurevych and Dan Roth and Amanda Stent},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-113572},
  doi =		{10.4230/DagRep.9.4.124},
  annote =	{Keywords: Information Consolidation, Multi-Document, NLP}

Keywords: Information Consolidation, Multi-Document, NLP
Collection: Dagstuhl Reports, Volume 9, Issue 4
Issue Date: 2019
Date of publication: 30.09.2019

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