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Flight crash investigation using data mining techniques

机译:使用数据挖掘技术进行空难调查

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Data mining refers to extraction of information from huge chunks of the dataset. It's also called information mining. It is exercised in numerous fields like medicine, environment, education, crime, etc. In this research work crash investigation and analysis of the flights are done. Flight crashes may be caused due to pilot error, mechanical failure, bad weather, sabotages or human error. This research paper investigates international flight crashes since 1908 to 2009 through K-Means clustering data mining technique and cosine similarity. Clustering helps to put objects into the same group. Cosine similarity measure helps in finding similarity among different texts. The research work is done for identifying aboard/ground fatality rate with operators and location as well as to find similarity among the plane crashes.
机译:数据挖掘是指从庞大的数据集中提取信息。这也称为信息挖掘。它在医学,环境,教育,犯罪等众多领域得到锻炼。在这项研究工作中,进行了坠机事故调查和航班分析。由于飞行员错误,机械故障,恶劣的天气,破坏或人为错误,可能导致航班坠毁。本研究论文通过K-Means聚类数据挖掘技术和余弦相似度研究了1908年至2009年以来的国际航班失事。群集有助于将对象放入同一组。余弦相似度度量有助于发现不同文本之间的相似度。这项研究工作是为了确定操作员和位置的机上/地面死亡率,以及在飞机失事之间寻找相似之处。

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