Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, Long Papers |
| Herausgeber/-innen | Phil Blunsom, Alexander Koller, Mirella Lapata |
| Seiten | 1117-1127 |
| Seitenumfang | 11 |
| Publikationsstatus | Veröffentlicht - Apr. 2017 |
| Extern publiziert | Ja |
| Veranstaltung | 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Valencia, Spanien Dauer: 3 Apr. 2017 → 7 Apr. 2017 |
Abstract
Future search engines are expected to deliver pro and con arguments in response to queries on controversial topics. While argument mining is now in the focus of research, the question of how to retrieve the relevant arguments remains open. This paper proposes a radical model to assess relevance objectively at web scale: The relevance of an argument's conclusion is decided by what other arguments reuse it as a premise. We build an argument graph for this model that we analyze with a recursive weighting scheme, adapting key ideas of PageRank. In experiments on a large ground-truth argument graph, the resulting relevance scores correlate with human average judgments. We outline what natural language challenges must be faced at web scale in order to stepwise bring argument relevance to web search engines.
ASJC Scopus Sachgebiete
- Sozialwissenschaften (insg.)
- Linguistik und Sprache
- Geisteswissenschaftliche Fächer (insg.)
- Sprache und Linguistik
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Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, Long Papers. Hrsg. / Phil Blunsom; Alexander Koller; Mirella Lapata. 2017. S. 1117-1127.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - “PageRank” for Argument Relevance
AU - Wachsmuth, Henning
AU - Stein, Benno
AU - Ajjour, Yamen
PY - 2017/4
Y1 - 2017/4
N2 - Future search engines are expected to deliver pro and con arguments in response to queries on controversial topics. While argument mining is now in the focus of research, the question of how to retrieve the relevant arguments remains open. This paper proposes a radical model to assess relevance objectively at web scale: The relevance of an argument's conclusion is decided by what other arguments reuse it as a premise. We build an argument graph for this model that we analyze with a recursive weighting scheme, adapting key ideas of PageRank. In experiments on a large ground-truth argument graph, the resulting relevance scores correlate with human average judgments. We outline what natural language challenges must be faced at web scale in order to stepwise bring argument relevance to web search engines.
AB - Future search engines are expected to deliver pro and con arguments in response to queries on controversial topics. While argument mining is now in the focus of research, the question of how to retrieve the relevant arguments remains open. This paper proposes a radical model to assess relevance objectively at web scale: The relevance of an argument's conclusion is decided by what other arguments reuse it as a premise. We build an argument graph for this model that we analyze with a recursive weighting scheme, adapting key ideas of PageRank. In experiments on a large ground-truth argument graph, the resulting relevance scores correlate with human average judgments. We outline what natural language challenges must be faced at web scale in order to stepwise bring argument relevance to web search engines.
UR - http://www.scopus.com/inward/record.url?scp=85021652808&partnerID=8YFLogxK
U2 - 10.18653/v1/e17-1105
DO - 10.18653/v1/e17-1105
M3 - Conference contribution
AN - SCOPUS:85021652808
SN - 9781510838604
SP - 1117
EP - 1127
BT - Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, Long Papers
A2 - Blunsom, Phil
A2 - Koller, Alexander
A2 - Lapata, Mirella
T2 - 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017
Y2 - 3 April 2017 through 7 April 2017
ER -