欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
异常点发现是从大量数据对象中挖掘少量具有异常行为模式的数据对象，很多情况下，这些数据对象较之正常行为模式包含了更多用户感兴趣的信息．该文针对某些具体应用领域中的数据对象具有高维性的特点，利用关联分析知识，提出一种高维空间异常点发现算法，理论分析和实验表明，算法是有效可行的．
英文摘要：
Discovery of outliers is to extract a few data objects with abnormal behavior patterns, which are more interesting than common patterns in some cases, from a large amount of data. It is of practical significance in intrusion detection systems, credit fraud detection, etc. Data in these domains are usually high dimensional, particularly featured by their sparseness and decline properties. An algorithm that can obtain the outliers with high efficiency is proposed based on association analysis. Effectiveness of the algorithm is shown by theory analysis and experiment results.
同期刊论文项目
同项目期刊论文
期刊信息
位置：