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International Biometric Society
A NEW APPROACH FOR STATISTICAL CLASSIFICATION AND VISUALIZATION
FOR LONGITUDINAL TEXT DATA
Shizue Izumi1 and Kenichi Satoh2
1 Department of Computer Science and Intelligent Systems, Oita University, Japan
2 Research Institute for Radiation Biology and Medicine, Hiroshima University, Japan
One of big data is longitudinally observed text data. Extraction of the time-varying trends of
keyword appearance and its classification can summarize the changes of characteristics in
longitudinal text data. Satoh and Tonda (2013) proposed the method of estimating
semiparametric varying coefficients using a mixed effects model. Here we propose a new
approach for statistical classification using a semiparametric regression model for the
keyword appearance in the longitudinally observed text data. And we suggest to visualize
the time-varying trends of keyword appearance using summary of predictors.
Keywords: Text mining, Summarization, Semiparametric model, Multi dimensional scaling.
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International Biometric Conference, Florence, ITALY, 6 – 11 July 2014