Anomalies are rare observations (eg, data records or events) that deviate significantly from
the others in the sample. Over the past few decades, research on anomaly mining has …

This paper provides a comprehensive survey of anomaly detection for the Internet of Things
(IoT). Anomaly detection poses numerous challenges in IoT, with broad applications …

Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …

Detecting outliers is a significant problem that has been studied in various research and
application areas. Researchers continue to design robust schemes to provide solutions to …

Stock prediction aims to predict the future trends of a stock in order to help investors make
good investment decisions. Traditional solutions for stock prediction are based on time …

Graph Anomaly Detection (GAD) is a technique used to identify abnormal nodes within
graphs, finding applications in network security, fraud detection, social media spam …

Due to its importance in several applications, including fraud and spammer detection,
anomaly detection has emerged as a key challenge in social network analysis in recent …

While many techniques for outlier detection have been proposed in the literature, the
interpretation of detected outliers is often left to users. As a result, it is difficult for users to …

Social media users are increasingly using both images and text to express their opinions
and share their experiences, instead of only using text in the conventional social media …

Anomaly detection is a crucial task in complex distributed systems. A thorough
understanding of the requirements and challenges of anomaly detection is pivotal to the …