Falke, Tobias ; Gurevych, Iryna (2019)
Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization.
The 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019). Minneapolis, USA (02.06.2019--07.10.2019)
doi: 10.18653/v1/N19-1074
Konferenzveröffentlichung, Bibliographie
Dies ist die neueste Version dieses Eintrags.
Kurzbeschreibung (Abstract)
Concept map-based multi-document summarization has recently been proposed as a variant of the traditional summarization task with graph-structured summaries. As shown by previous work, the grouping of coreferent concept mentions across documents is a crucial subtask of it. However, while the current state-of-the-art method suggested a new grouping method that was shown to improve the summary quality, its use of pairwise comparisons leads to polynomial runtime complexity that prohibits the application to large document collections. In this paper, we propose two alternative grouping techniques based on locality sensitive hashing, approximate nearest neighbor search and a fast clustering algorithm. They exhibit linear and log-linear runtime complexity, making them much more scalable. We report experimental results that confirm the improved runtime behavior while also showing that the quality of the summary concept maps remains comparable.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Falke, Tobias ; Gurevych, Iryna |
| Art des Eintrags: | Bibliographie |
| Titel: | Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization |
| Sprache: | Englisch |
| Publikationsjahr: | 27 Februar 2019 |
| Ort: | Minneapolis, Minnesota |
| Verlag: | Association for Computational Linguistics |
| Buchtitel: | Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) |
| Veranstaltungstitel: | The 2019 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019) |
| Veranstaltungsort: | Minneapolis, USA |
| Veranstaltungsdatum: | 02.06.2019--07.10.2019 |
| DOI: | 10.18653/v1/N19-1074 |
| URL / URN: | https://aclanthology.org/N19-1074 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Concept map-based multi-document summarization has recently been proposed as a variant of the traditional summarization task with graph-structured summaries. As shown by previous work, the grouping of coreferent concept mentions across documents is a crucial subtask of it. However, while the current state-of-the-art method suggested a new grouping method that was shown to improve the summary quality, its use of pairwise comparisons leads to polynomial runtime complexity that prohibits the application to large document collections. In this paper, we propose two alternative grouping techniques based on locality sensitive hashing, approximate nearest neighbor search and a fast clustering algorithm. They exhibit linear and log-linear runtime complexity, making them much more scalable. We report experimental results that confirm the improved runtime behavior while also showing that the quality of the summary concept maps remains comparable. |
| Freie Schlagworte: | AIPHES;UKP_reviewed |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen |
| Hinterlegungsdatum: | 18 Sep 2019 12:13 |
| Letzte Änderung: | 11 Jun 2024 07:17 |
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| Suche nach Titel in: | TUfind oder in Google |
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Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization. (deposited 27 Feb 2019 10:04)
- Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization. (deposited 18 Sep 2019 12:13) [Gegenwärtig angezeigt]
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