6 papers
Stochastic Voronoi Ensembles for Anomaly Detection
Yang Cao, Sikun Yang, Xuyun Zhang +1
Anomaly detection aims to identify data instances that deviate significantly from majority of data, which has been widely used in fraud detection, network security, and industrial…
Towards Token-Level Text Anomaly Detection
Yang Cao, Bicheng Yu, Sikun Yang +2
Despite significant progress in text anomaly detection for web applications such as spam filtering and fake news detection, existing methods are fundamentally limited to document-l…
Kernel Representation and Similarity Measure for Incomplete Data
Yang Cao, Sikun Yang, Kai He +4
Measuring similarity between incomplete data is a fundamental challenge in web mining, recommendation systems, and user behavior analysis. Traditional approaches either discard inc…
Isolation-based Spherical Ensemble Representations for Anomaly Detection
Yang Cao, Sikun Yang, Hao Tian +4
Anomaly detection is a critical task in data mining and management with applications spanning fraud detection, network security, and log monitoring. Despite extensive research, exi…
Text Anomaly Detection with Simplified Isolation Kernel
Yang Cao, Sikun Yang, Yujiu Yang +2
Two-step approaches combining pre-trained large language model embeddings and anomaly detectors demonstrate strong performance in text anomaly detection by leveraging rich semantic…
TAD-Bench: A Comprehensive Benchmark for Embedding-Based Text Anomaly Detection
Yang Cao, Sikun Yang, Chen Li +5
Text anomaly detection is crucial for identifying spam, misinformation, and offensive language in natural language processing tasks. Despite the growing adoption of embedding-based…