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
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2019/11357/
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)
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.
BibTeX - Entry
@Article{daga_et_al:DR:2019:11357,
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 = {http://drops.dagstuhl.de/opus/volltexte/2019/11357},
URN = {urn:nbn:de:0030-drops-113572},
doi = {10.4230/DagRep.9.4.124},
annote = {Keywords: Information Consolidation, Multi-Document, NLP}
}
Keywords: |
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Information Consolidation, Multi-Document, NLP |
Collection: |
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Dagstuhl Reports, Volume 9, Issue 4 |
Issue Date: |
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2019 |
Date of publication: |
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30.09.2019 |