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

Content Provider	IEEE Xplore Digital Library
Author	Dong Ren Long Ma Yanqing Zhang Sunderraman, R. Fox, P.T. Laird, A.R. Turner, J.A. Turner, M.D.
Copyright Year	2015
Description	Author affiliation: Health Sci. Center, Univ. of Texas, San Antonio, TX, USA (Fox, P.T.) \|\| Depts. of Comput. Sci. & Psychol., Georgia State Univ., Atlanta, GA, USA (Turner, M.D.) \|\| Dept. of Phys., Florida Int. Univ., Miami, FL, USA (Laird, A.R.) \|\| Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA (Dong Ren; Long Ma; Yanqing Zhang; Sunderraman, R.) \|\| Dept. of Psychol. & the Neurosci. Inst., Georgia State Univ., Atlanta, GA, USA (Turner, J.A.)
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.
Starting Page	234
Ending Page	241
File Size	762045
Page Count	8
File Format	PDF
e-ISBN	9781467372909
DOI	10.1109/ICCI-CC.2015.7259391
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Classification algorithms Bagging Testing Metadata World Wide Web Gold multi-label classification text mining text annotation neuroinformatics multi-instance multi-label classification feature reduction
Content Type	Text
Resource Type	Article

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