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首页> 外文会议>International Symposium on Computer and Information Sciences(ISCIS 2004); 20041027-29; Kemer-Antalya(TR) >Investigating the Effects of Recency and Size of Training Text on Author Recognition Problem
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Investigating the Effects of Recency and Size of Training Text on Author Recognition Problem

机译：调查最近度和培训文字的大小对作者识别问题的影响

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摘要

Prediction by partial match (PPM) is an effective tool to address the author recognition problem. In this study, we have successfully applied the trained PPM technique for author recognition on Turkish texts. Furthermore, we have investigated the effects of recency, as well as size of the training text on the performance of the PPM approach. Results show that, more recent and larger training texts help decrease the compression rate, which, in turn, leads to increased success in author recognition. Comparing the effects of the recency and the size of the training text, we see that the size factor plays a more dominant role on the performance.
机译：部分匹配预测（PPM）是解决作者识别问题的有效工具。在这项研究中，我们成功地将训练有素的PPM技术应用于土耳其文字的作者识别。此外，我们研究了新近度的影响以及培训文本的大小对PPM方法的效果。结果表明，更新的和更大的培训课本有助于降低压缩率，从而提高作者识别的成功率。比较新近度和训练文本大小的影响，我们发现大小因子在性能上起更主要的作用。

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