• Medientyp: Sonstige Veröffentlichung; E-Artikel
  • Titel: Multi-Document Information Consolidation (Dagstuhl Seminar 19182)
  • Beteiligte: Daga, Ido [VerfasserIn]; Gurevych, Iryna [VerfasserIn]; Roth, Dan [VerfasserIn]; Stent, Amanda [VerfasserIn]
  • Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2019
  • Sprache: Englisch
  • DOI: https://doi.org/10.4230/DagRep.9.4.124
  • Schlagwörter: NLP ; Information Consolidation ; Multi-Document
  • Entstehung:
  • Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Beschreibung: 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.
  • Zugangsstatus: Freier Zugang