Multi-Document Information Consolidation (Dagstuhl Seminar 19182)

Authors Ido Daga, Iryna Gurevych, Dan Roth, Amanda Stent and all authors of the abstracts in this report

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Ido Daga
Iryna Gurevych
Dan Roth
Amanda Stent
and all authors of the abstracts in this report

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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)


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.
  • Information Consolidation
  • Multi-Document
  • NLP


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