Handling uncertainty in relation extraction: a case study on tennis tournament results extraction from tweets

J. Verburg; M. B. Habib; M. van Keulen

doi:10.1145/2815833.2816960

Handling uncertainty in relation extraction: a case study on tennis tournament results extraction from tweets

J. Verburg, M. B. Habib, M. van Keulen

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

Abstract

Relation extraction involves different types of uncertainty due to the imperfection of the extraction tools and the inherent ambiguity of unstructured text. In this paper, we discuss several ways of handling uncertainties in relation extraction from social media. Our study case is to extract tennis games' results for two Grand Slam tennis tournaments from tweets. Analysis has been done to find to what extent it is useful to use semantic web, domain knowledge, facts repetition, and authors' trustworthiness to improve the certainty of the extracted relations.

Original language	English
Title of host publication	Proceedings of the 8th International Conference on Knowledge Capture (K-CAP 2015), New York, USA
Place of Publication	New York
Publisher	The Association for Computing Machinery
Pages	Article No. 26
DOIs	https://doi.org/10.1145/2815833.2816960
Publication status	Published - 1 Oct 2015
Externally published	Yes

Keywords

Relation Extraction
Uncertainty Analysis
Semantic Web
Social Media
Tennis tournament
Named Entity Recognition
Named Entity Linking
Twitter

Access to Document

10.1145/2815833.2816960

Cite this

@inproceedings{ccb544a35f114f2581d2cdd06307664f,

title = "Handling uncertainty in relation extraction: a case study on tennis tournament results extraction from tweets",

abstract = "Relation extraction involves different types of uncertainty due to the imperfection of the extraction tools and the inherent ambiguity of unstructured text. In this paper, we discuss several ways of handling uncertainties in relation extraction from social media. Our study case is to extract tennis games' results for two Grand Slam tennis tournaments from tweets. Analysis has been done to find to what extent it is useful to use semantic web, domain knowledge, facts repetition, and authors' trustworthiness to improve the certainty of the extracted relations.",

keywords = "Relation Extraction, Uncertainty Analysis, Semantic Web, Social Media, Tennis tournament, Named Entity Recognition, Named Entity Linking, Twitter",

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Handling uncertainty in relation extraction: a case study on tennis tournament results extraction from tweets. / Verburg, J.; Habib, M. B.; Keulen, M. van.
Proceedings of the 8th International Conference on Knowledge Capture (K-CAP 2015), New York, USA. New York: The Association for Computing Machinery, 2015. p. Article No. 26.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceeding › Academic › peer-review

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KW - Relation Extraction

KW - Uncertainty Analysis

KW - Semantic Web

KW - Social Media

KW - Tennis tournament

KW - Named Entity Recognition

KW - Named Entity Linking

KW - Twitter

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