Feature Grouping-Based Outlier Detection Upon Streaming Trajectories
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2017.2744619
Abstract: Outlier detection acts as one of the most important analysis tasks for trajectory stream. In stream scenarios, such properties as unlimitedness, time-varying evolutionary, sparsity, and skewness distribution of trajectories pose new challenges to outlier detection… read more here.
Keywords: detection; based outlier; grouping based; feature grouping ... See more keywords
Weighted Outlier Detection of High-Dimensional Categorical Data Using Feature Grouping
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"
DOI: 10.1109/tsmc.2018.2847625
Abstract: We propose a weighted outlier mining method called WATCH to identify outliers in high-dimensional categorical datasets. WATCH is composed of two distinctive modules: 1) feature grouping by the virtue of correlation measurement among features and… read more here.
Keywords: weighted outlier; outlier mining; dimensional categorical; high dimensional ... See more keywords