Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
Special Section on Recent Progress in Nonlinear Theory and Its Applications
Micro-text classification between small and big data
Markus ChristenThomas NiederbergerThomas OttSuleiman AryobseiReto Hofstetter
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2015 Volume 6 Issue 4 Pages 556-569

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Abstract

Micro-texts emerging from social media platforms have become an important source for research. Automatized classification and interpretation of such micro-texts is challenging. The problem is exaggerated if the number of texts is at a medium level, making it too small for effective machine learning, but too big to be efficiently analyzed solely by humans. We present a semi-supervised learning system for micro-text classification that combines machine learning techniques with the unmatched human ability for making demanding, i.e. nonlinear decisions based on sparse data. We compare our system with human performance and a predefined optimal classifier using a validated benchmark data-set.

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© 2015 The Institute of Electronics, Information and Communication Engineers
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