Clustering analysis' primary purpose is to divide a dataset into a finite number of segments
based on the similarities between items. In recent years, a significant amount of study has …

Real-time recognition and prediction of surgical activities are fundamental to advancing
safety and autonomy in robot-assisted surgery. This paper presents a multimodal …

A persistent item in a stream is one that occurs regularly in the stream without necessarily
contributing significantly to the volume of the stream. Persistent items are often associated …

Event data analysis is becoming increasingly of interest to academic researchers looking for
patterns in the data. Unlike domain experts working in large companies who have access to …

Data science has recently gained much attention for a number of reasons, and among them
is Big Data. Scientists (from almost all disciplines including physics, chemistry, biology …

Querying streams of data from the sensors or other devices requires several operators. One
of the most important operators is called Windowing. Creating windows consists in grouping …

Data stream processing is an increasingly important topic due to the prevalence of smart
devices and the demand for real-time analytics. Geo-distributed streaming systems, where …

Handling timestamp-disorder among stream tuples is a basic requirement for data stream
processing, and involves an inevitable tradeoff between the latency and the quality of stream …

Abstract Systems for managing content in a cloud-based service platform. Procedures for
deduplication of a shared object in a cloud-based environment having one or more storage …

RFID technology and the Internet of Things provide a flood of information which can be
regarded as a stream of complex events. The most acute complex event data management …