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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
Conference or Workshop Item, Bibliographie

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.

Item Type: Conference or Workshop Item
Erschienen: 2017
Creators: Falke, Tobias ; Gurevych, Iryna
Type of entry: Bibliographie
Title: Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps
Language: English
Date: September 2017
Book Title: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Event Location: Copenhagen, Denmark
URL / URN: http://aclweb.org/anthology/D17-1320
Corresponding Links:
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.

Uncontrolled Keywords: UKP_reviewed;AIPHES_corpus;AIPHES_area_b1
Identification Number: TUD-CS-2017-0153
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Ubiquitous Knowledge Processing
DFG-Graduiertenkollegs
DFG-Graduiertenkollegs > Research Training Group 1994 Adaptive Preparation of Information from Heterogeneous Sources
Date Deposited: 04 Jul 2017 14:17
Last Modified: 24 Jan 2020 12:03
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