Details
| Original language | English |
|---|---|
| Title of host publication | SIGIR 2020 |
| Subtitle of host publication | Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval |
| Place of Publication | New York |
| Pages | 1969-1972 |
| Number of pages | 4 |
| Publication status | Published - 25 Jul 2020 |
| Externally published | Yes |
| Event | 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 - Virtual, Online, China Duration: 25 Jul 2020 → 30 Jul 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.
Keywords
- argument search, argumentation, snippet generation
ASJC Scopus subject areas
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
- Computer Science(all)
- Information Systems
- Computer Science(all)
- Software
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
SIGIR 2020: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, 2020. p. 1969-1972.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Extractive Snippet Generation for Arguments
AU - Alshomary, Milad
AU - Düsterhus, Nick
AU - Wachsmuth, Henning
PY - 2020/7/25
Y1 - 2020/7/25
N2 - 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.
AB - 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.
KW - argument search
KW - argumentation
KW - snippet generation
UR - http://www.scopus.com/inward/record.url?scp=85090132219&partnerID=8YFLogxK
U2 - 10.1145/3397271.3401186
DO - 10.1145/3397271.3401186
M3 - Conference contribution
AN - SCOPUS:85090132219
SN - 9781450380164
SP - 1969
EP - 1972
BT - SIGIR 2020
CY - New York
T2 - 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020
Y2 - 25 July 2020 through 30 July 2020
ER -