Automated Dataset Construction from Web Resources with Tool Kayur

Alexander Kohan, M. Yamamoto, Cyrille Artho
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引用次数: 1

Abstract

Many text mining tools cannot be applied directly to documents available on web pages. There are tools for fetching and preprocessing of textual data, but combining them in one working tool chain can be time consuming. The preprocessing task is even more labor-intensive if documents are located on multiple remote sources with different storage formats. In this paper we propose the simplification of data preparation process for cases when data come from wide range of web resources. We developed an open-sourced tool, called Kayur, that greatly minimizes time and effort required for routine data preprocessing steps, allowing to quickly proceed to the main task of data analysis. The datasets generated by the tool are ready to be loaded into a data mining workbench, such as WEKA or Carrot2, to perform classification, feature prediction, and other data mining tasks.
使用工具Kayur从Web资源自动构建数据集
许多文本挖掘工具不能直接应用于网页上可用的文档。有一些工具用于获取和预处理文本数据,但是将它们组合在一个工作工具链中可能会非常耗时。如果文档位于具有不同存储格式的多个远程数据源上,那么预处理任务将更加耗费人力。在本文中,我们提出了一种简化数据准备过程的方法,适用于数据来自多种网络资源的情况。我们开发了一个名为Kayur的开源工具,它极大地减少了常规数据预处理步骤所需的时间和精力,允许快速进行数据分析的主要任务。工具生成的数据集可以加载到数据挖掘工作台(如WEKA或Carrot2)中,以执行分类、特征预测和其他数据挖掘任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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