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Big Text advantages and challenges: classification perspective

  • Marina SokolovaEmail author
Trends of Data Science

Abstract

Big Text, i.e., large repositories of textual data, is a part of Big Data. In total, 80–85 % of Big Text comes in unstructured form, with significant contribution from social media. In this position paper, we discuss Big Text advantages and challenges in respect to text classification. We propose a new approach to performance evaluation of classification algorithms when they applied to Big Text, namely, using corpora comparison in the result evaluation. We also discuss a significant increase in texts with comprehensive information and challenges Big Text methods face in analysis of such texts.

Keywords

Big text Machine learning Classification Performance evaluation 

Notes

Acknowledgements

The author thanks anonymous reviewers for helpful comments.

Conflict of interest

The author states that there is no conflict of interest.

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Authors and Affiliations

  1. 1.School of Epidemiology and Public HealthOttawaCanada

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