Classification of Text Documents based on Naive Bayes using N-Gram Features

Document classification is basically the process of categorizing documents in certain categories correctly. This process, which is usually used in the field of text mining, automatically classifies documents with large dimensions. In this paper, Turkish document classification was performed by using...

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Bibliographic Details
Published in2018 International Conference on Artificial Intelligence and Data Processing (IDAP) pp. 1 - 5
Main Author BAYGIN, Mehmet
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2018
Subjects
Bayes methods
Data mining
document classification
Feature extraction
Machine learning
Naïve Bayes
Sentiment analysis
Sports
Training
Online AccessGet full text
DOI10.1109/IDAP.2018.8620853

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Summary:Document classification is basically the process of categorizing documents in certain categories correctly. This process, which is usually used in the field of text mining, automatically classifies documents with large dimensions. In this paper, Turkish document classification was performed by using Naïve Bayes approach which is one of the machine learning methods. With this approach, which basically uses 5 different categories, Turkish documents are classified quickly and automatically. In addition, the performance of the proposed approach was measured according to the basic evaluation criteria of precision, recall, accuracy and f-measure, and achieved a success rate of 92%. Also, the source codes of the application developed in this paper are presented as open source at https://drive.google.com/open?id=1Idp5VK1Q91vyqb940WjeoMpB9dVQuVC9.
DOI:10.1109/IDAP.2018.8620853