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Biological entity relationship extraction method based on multiple kernel learning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The authors combine feature-based kernel with extension path graph kernel into a multiple kernels learning method. Feature-based kernel method, extension path graph kernel method and multiple kernels learning method are conducted on experiment on the most authoritative five evaluation corpuses. Experimental results indicate that the performance of the fused kernel method in five corpus sets is superior to that of the two separate single-kernel method.

Original languageEnglish
Title of host publicationProceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
EditorsKevin Burrage, Qian Zhu, Yunlong Liu, Tianhai Tian, Yadong Wang, Xiaohua Tony Hu, Qinghua Jiang, Jiangning Song, Shinichi Morishita, Kevin Burrage, Guohua Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1669-1672
Number of pages4
ISBN (Electronic)9781509016105
DOIs
StatePublished - 17 Jan 2017
Externally publishedYes
Event2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016 - Shenzhen, China
Duration: 15 Dec 201618 Dec 2016

Publication series

NameProceedings - 2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

Conference

Conference2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016
Country/TerritoryChina
CityShenzhen
Period15/12/1618/12/16

Keywords

  • Entity Relationship Extraction
  • Information extraction
  • Multiple Kernels Learning

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