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.
@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.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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