High precision rule based ppi extraction and per-pair basis performance evaluation

Junkyu Lee, Seongsoon Kim, Sunwon Lee, Kyubum Lee, Jaewoo Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Virtually all current PPI extraction studies focus on improving F-score, aiming to balance the performance on both precision and recall. However, in many realistic scenarios involving large corpora, one can benefit more from an extremely high precision PPI extraction tool than a high-recall counterpart. We also argue that the current per-instance basis performance evaluation method should be revisited. In order to address these problems, we introduce a new rulebased PPI extraction method equipped with a set of ultrahigh precision extraction rules. We also propose a new perpair basis performance metric, which is more pragmatic in practice. The proposed PPI extraction method achieves 95-96% per-pair and 94-97% per-instance precisions on the AIMed benchmark corpus.

Original languageEnglish
Title of host publicationDTMBIO'12 - Proceedings of the 6th ACM International Workshop on Data and Text Mining in Biomedical Informatics, Co-located with CIKM 2012
Pages69-76
Number of pages8
DOIs
Publication statusPublished - 2012
Event6th ACM International Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO 2012, in Conjunction with the 21st ACM International Conference on Information and Knowledge Management, CIKM 2012 - Maui, HI, United States
Duration: 2012 Oct 292012 Oct 29

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Other

Other6th ACM International Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO 2012, in Conjunction with the 21st ACM International Conference on Information and Knowledge Management, CIKM 2012
Country/TerritoryUnited States
CityMaui, HI
Period12/10/2912/10/29

Keywords

  • Biomedical Text Mining
  • Entity Relation Extraction
  • Interaction Extraction
  • PPI
  • Text Mining

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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