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Authorship Attribution Analysis of Thai Online Messages

机译:泰国在线消息的作者归因分析

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This paper presents a framework to identify the authors of Thai online messages. The identification is based on 53 writing attributes and the selected algorithms are support vector machine (SVM) and C4.5 decision tree. Experimental results indicate that the overall accuracies achieved by the SVM and the C4.5 were 79% and 75%, respectively. This difference was not statistically significant (at 95% confidence interval). As for the performance of identifying individual authors, in some cases the SVM was clearly better than the C4.5. But there were also other cases where both of them could not distinguish one author from another.
机译:本文介绍了识别泰国在线消息的作者的框架。该标识基于53写入属性,并且所选算法是支持向量机(SVM)和C4.5决策树。实验结果表明,SVM和C4.5实现的整体准确性分别为79%和75%。这种差异没有统计学意义(95%置信区间)。至于识别单个作者的表现,在某些情况下,SVM显然比C4.5更好。但还有其他情况,其中两者都无法将一个作者与另一个作​​者区分开来。

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