论文标题
一项关于外围方面挖掘方法的综合调查
A Comprehensive Survey on Outlying Aspect Mining Methods
论文作者
论文摘要
近年来，研究人员对挖掘方面越来越感兴趣。外围方面挖掘是找到一组功能的任务，其中给定的数据对象与其余数据对象不同。很少有人设计研究来解决挖掘方面的问题。因此，关于研究人员之间的外观挖掘方法及其优势和劣势知之甚少。在这项工作中，我们将现有的外围方面挖掘方法分为三种不同类别。对于每个类别，我们提供了属于该类别的现有工作，然后在这些类别中提供了优点和劣势。我们还提供了当前技术的时间复杂性比较，因为这是现实情况下的关键问题。本文背后的动机是更好地了解现有的外围方面挖掘技术以及如何开发这些技术。
In recent years, researchers have become increasingly interested in outlying aspect mining. Outlying aspect mining is the task of finding a set of feature(s), where a given data object is different from the rest of the data objects. Remarkably few studies have been designed to address the problem of outlying aspect mining; therefore, little is known about outlying aspect mining approaches and their strengths and weaknesses among researchers. In this work, we have grouped existing outlying aspect mining approaches in three different categories. For each category, we have provided existing work that falls in that category and then provided their strengths and weaknesses in those categories. We also offer time complexity comparison of the current techniques since it is a crucial issue in the real-world scenario. The motive behind this paper is to give a better understanding of the existing outlying aspect mining techniques and how these techniques have been developed.
