Identifying trendline visualizations with desired patterns is a common task during data
exploration. Existing visual analytics tools offer limited flexibility, expressiveness, and …

Anomaly detection is a fundamental problem that consists of identifying irregular patterns
that do not conform to the expected behavior of a system or the generated data. Many …

Interactive data exploration (IDE) is an effective way of comprehending big data, whose
volume and complexity are beyond human abilities. The main goal of IDE is to discover user …

This paper presents AnoViz, a novel visualization tool of anomalies in multivariate time
series, to support domain experts and data scientists in understanding anomalous instances …

摘要工业大数据已经成为我国制造业转型升级的重要战略资源, 工业大数据分析问题正引起重视
和关注. 时序数据作为工业大数据中一种重要的数据形式, 存在大量的数据质量问题 …

Fault detection is essential to ensure the proper operation of solar-thermal plants. Hence,
monitoring personnel frequently analyze the data to detect unusual behavior. While …

In this demo, we introduce Exathlon-a new benchmarking platform for explainable anomaly
detection over high-dimensional time series. We designed Exathlon to support data …

Wireless Sensor Networks (WSN) use many sensor nodes to monitor various environmental
information in designated areas in real-time, which has broad application prospects in many …

In this research, a hybrid approach combining a Hidden Markov Model (HMM) with a Long
Short-Term Memory (LSTM) recurrent neural network (RNN) is introduced to model real-time …

Temporal data refer to historical data, where data items have additional temporal semantics,
ie, the time periods during which the data represent true facts in the real world. This type of …