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Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps

Falke, Tobias ; Gurevych, Iryna (2017)
Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps.
Copenhagen, Denmark
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Concept maps can be used to concisely represent important information and bring structure into large document collections. Therefore, we study a variant of multi-document summarization that produces summaries in the form of concept maps. However, suitable evaluation datasets for this task are currently missing. To close this gap, we present a newly created corpus of concept maps that summarize heterogeneous collections of web documents on educational topics. It was created using a novel crowdsourcing approach that allows us to efficiently determine important elements in large document collections. We release the corpus along with a baseline system and proposed evaluation protocol to enable further research on this variant of summarization.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2017
Autor(en): Falke, Tobias ; Gurevych, Iryna
Art des Eintrags: Bibliographie
Titel: Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps
Sprache: Englisch
Publikationsjahr: September 2017
Buchtitel: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Veranstaltungsort: Copenhagen, Denmark
URL / URN: http://aclweb.org/anthology/D17-1320
Zugehörige Links:
Kurzbeschreibung (Abstract):

Concept maps can be used to concisely represent important information and bring structure into large document collections. Therefore, we study a variant of multi-document summarization that produces summaries in the form of concept maps. However, suitable evaluation datasets for this task are currently missing. To close this gap, we present a newly created corpus of concept maps that summarize heterogeneous collections of web documents on educational topics. It was created using a novel crowdsourcing approach that allows us to efficiently determine important elements in large document collections. We release the corpus along with a baseline system and proposed evaluation protocol to enable further research on this variant of summarization.

Freie Schlagworte: UKP_reviewed;AIPHES_corpus;AIPHES_area_b1
ID-Nummer: TUD-CS-2017-0153
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen
Hinterlegungsdatum: 04 Jul 2017 14:17
Letzte Änderung: 24 Jan 2020 12:03
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