Text Classification Using Data Mining Techniques: A Review
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Date
2018-05
Journal Title
Journal ISSN
Volume Title
Publisher
School of Computing, Engineering and Physical Science, University of the West of Scotland, Paisley.
Abstract
mining algorithms used for text classification and a
review of works that have been performed on
classifying texts.
Design/Methodology/Approach: Data mining
algorithms used for text classification were discussed
and researches done on applying such algorithms in
classifying texts were considered with more
emphasis on comparative studies.
Findings: No classifier can perform best in all
situations as different datasets and conditions bring
about different classification accuracies.
Practical Implications: In applying data mining
algorithms for classifying text documents, it should
be noted that the conditions of the data will affect
classification accuracy; therefore such data should be
well presented. Researchers may also need to try
different algorithms and conditions to get a desired
level of accuracy.
Originality/Value: A lot of work has been done in
reviewing of data mining algorithms but this research
has its specific emphasis on text and in addition to
previous reviews, more recent journals were
considered
Description
Keywords
Data mining, Text mining, text classification, performance evaluation, classifier, machine learning algorithm (MLA).
Citation
Abikoye, O.C., Omokanye, S.O. & Aro, T.O. (2018): Text Classification Using Data Mining Techniques: A Review. Computing and Information Systems Journal. 22(2); 1- 8, Published by School of Computing, Engineering and Physical Science, University of the West of Scotland, Paisley.