基于小世界模型对异常数据的分析技术  

Analysis of Outliers Data based on Small-World Effect

作　　者：谢杰[1] 

机构地区：[1]上海交通大学信息安全工程学院,上海200240

出　　处：《信息安全与通信保密》2014年第1期75-77,82,共4页Information Security and Communications Privacy

摘　　要：随着Internet的飞速发展以及宽带无线网络的出现,面对日增月积的网络海量数据,如何有效地应用模型进行数据分析,根据分析意图、目的简明直接地得到所关心的结果,成为关注的重点。当前,小世界模型在中国越来越被重视,并被有效地运用至网络、医药、生物、企业等各个领域。因此,以小世界模型作为理论依据,进一步扩展数据聚类的功能,讨论切实、高效地获取异常数据分析的技术,就显得尤为必要。With the rapid development of Internet and the presence of board-band and in the face of massive network data, how to implement data analysis with efficient model and how to get the expectant result directly become the focal points. At present, the small world effect attracts much attention in China, and is applied in various fields effectively, including network, medicine, biology, and business etc. For these reason, with small-world effect as the theoretical basis, the technology in efficiently obtaining the outlier-data analysis is discussed, thus to further expand the function of clustering data.

关 键 词：小世界模型 数据分析 异常数据 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]