Outlier detection in complex categorical data by modeling the feature value couplings

• Main Authors: PANG, Guansong, CAO, Longbing, CHEN, Ling
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Databases and Information Systems; Data Storage Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/7146; https://ink.library.smu.edu.sg/context/sis_research/article/8149/viewcontent/272.pdf
• Institution: Singapore Management University

This paper introduces a novel unsupervised outlier detection method, namely Coupled Biased Random Walks (CBRW), for identifying outliers in categorical data with diversified frequency distributions and many noisy features. Existing pattern-based outlier detection methods are ineffective in handling...