Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …

Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …

Abstract Number of connected devices is steadily increasing and these devices continuously
generate data streams. Real-time processing of data streams is arousing interest despite …

Nowadays, with the advance of technology, many applications generate huge amounts of
data streams at very high speed. Examples include network traffic, web click streams, video …

Twitter is a popular online social network with hundreds of millions of users, where n
important part of the accounts in this social network are not humans. Approximately 48 …

Clustering data streams has drawn lots of attention in the last few years due to their ever-
growing presence. Data streams put additional challenges on clustering such as limited time …

In recent times there has been an increase in data availability in continuous data streams
and clustering of this data has many advantages in data analysis. It is often the case that …

As more and more applications produce streaming data, clustering data streams has
become an important technique for data and knowledge engineering. A typical approach is …

Clustering algorithms have become one of the most critical research areas in multiple
domains, especially data mining. However, with the massive growth of big data applications …

A data stream is a continuously arriving sequence of data and clustering data streams
requires additional considerations to traditional clustering. A stream is potentially …