Extractive Snippet Generation for Arguments

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

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  • Universität Paderborn
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OriginalspracheEnglisch
Titel des SammelwerksSIGIR 2020
Untertitel Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval
ErscheinungsortNew York
Seiten1969-1972
Seitenumfang4
PublikationsstatusVeröffentlicht - 25 Juli 2020
Extern publiziertJa
Veranstaltung43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 - Virtual, Online, China
Dauer: 25 Juli 202030 Juli 2020

Abstract

Snippets are used in web search to help users assess the relevance of retrieved results to their query. Recently, specialized search engines have arisen that retrieve pro and con arguments on controversial issues. We argue that standard snippet generation is insufficient to represent the core reasoning of an argument. In this paper, we introduce the task of generating a snippet that represents the main claim and reason of an argument. We propose a query-independent extractive summarization approach to this task that uses a variant of PageRank to assess the importance of sentences based on their context and argumentativeness. In both automatic and manual evaluation, our approach outperforms strong baselines.

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Extractive Snippet Generation for Arguments. / Alshomary, Milad; Düsterhus, Nick; Wachsmuth, Henning.
SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, 2020. S. 1969-1972.

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Alshomary, M, Düsterhus, N & Wachsmuth, H 2020, Extractive Snippet Generation for Arguments. in SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, S. 1969-1972, 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020, Virtual, Online, China, 25 Juli 2020. https://doi.org/10.1145/3397271.3401186
Alshomary, M., Düsterhus, N., & Wachsmuth, H. (2020). Extractive Snippet Generation for Arguments. In SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (S. 1969-1972). https://doi.org/10.1145/3397271.3401186
Alshomary M, Düsterhus N, Wachsmuth H. Extractive Snippet Generation for Arguments. in SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York. 2020. S. 1969-1972 doi: 10.1145/3397271.3401186
Alshomary, Milad ; Düsterhus, Nick ; Wachsmuth, Henning. / Extractive Snippet Generation for Arguments. SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, 2020. S. 1969-1972
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