Detecting Anomaly Collections using Extreme Feature Ranks

• المؤلفون الرئيسيون: DAI, Hanbo, ZHU, Feida, LIM, Ee Peng, PANG, Hwee Hwa
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2014
• الموضوعات: Anomaly collection; Extreme feature rank; Anomaly cluster; Outlier group; Spam detection; Spam cluster; Computer Sciences; Databases and Information Systems
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/2534; https://ink.library.smu.edu.sg/context/sis_research/article/3534/viewcontent/Detecting_Anomaly_Collections_using_Extreme_Feature_Ranks__edited_.pdf
• المؤسسة: Singapore Management University

Detecting anomaly collections is an important task with many applications, including spam and fraud detection. In an anomaly collection, entities often operate in collusion and hold different agendas to normal entities. As a result, they usually manifest collective extreme traits, i.e., members of a...