Online biomedical publication classification using Multi-Instance Multi-Label algorithms with feature reduction

Dong Ren, Long Ma, Yanqing Zhang, Raj Sunderraman, Peter T Fox, Angela R. Laird, Jessica A. Turner, Matthew D. Turner

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

5 Scopus citations

Abstract

Text annotation, the assignment of metadata to documents, requires significant time and effort when performed by humans. A variety of text mining methods have been used to automate this process, many of them based on either keyword extraction or word counts. However, when using keywords as text classification features, it is common to find that (1) the number of training instances is much less than the number of features extracted. This complexity affects text classification performance. Another challenge is (2) the assignment of multiple, non-exclusive labels to the documents (multi-label classification). This problem makes text classification more complicated when compared with single label classification. We use, as an example, a set of expertly labeled documents from the human functional neuroimaging literature, and we apply a Multi-instance Multi-label (MIML) classification algorithm to the problem. To address (1), we apply a feature reduction approach to reduce the feature dimension. For (2) we use an MIML algorithm called MIMLfast to implement the multi-label classification.

Original languageEnglish (US)
Title of host publicationProceedings of 2015 IEEE 14th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages234-241
Number of pages8
ISBN (Print)9781467372893
DOIs
StatePublished - Sep 11 2015
Event14th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2015 - Beijing, China
Duration: Jul 6 2015Jul 8 2015

Other

Other14th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2015
CountryChina
CityBeijing
Period7/6/157/8/15

Keywords

  • feature reduction
  • multi-instance multi-label classification
  • multi-label classification
  • neuroinformatics
  • text annotation
  • text mining

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Experimental and Cognitive Psychology

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  • Cite this

    Ren, D., Ma, L., Zhang, Y., Sunderraman, R., Fox, P. T., Laird, A. R., Turner, J. A., & Turner, M. D. (2015). Online biomedical publication classification using Multi-Instance Multi-Label algorithms with feature reduction. In Proceedings of 2015 IEEE 14th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2015 (pp. 234-241). [7259391] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCI-CC.2015.7259391