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 proceedingConference article in proceedingAcademicpeer-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 languageEnglish
Title of host publicationProceedings of the 8th International Conference on Knowledge Capture (K-CAP 2015), New York, USA
Place of PublicationNew York
PublisherACM
PagesArticle No. 26
Publication statusPublished - 1 Oct 2015

Keywords

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

Cite this

Verburg, J., Habib, M. B., & Keulen, M. V. (2015). Handling uncertainty in relation extraction: a case study on tennis tournament results extraction from tweets. In Proceedings of the 8th International Conference on Knowledge Capture (K-CAP 2015), New York, USA (pp. Article No. 26). ACM.