In the current age of the Fourth Industrial Revolution (4 IR or Industry 4.0), the digital world
has a wealth of data, such as Internet of Things (IoT) data, cybersecurity data, mobile data …

Data analysis is used as a common method in modern science research, which is across
communication science, computer science and biology science. Clustering, as the basic …

At SIGMOD 2015, an article was presented with the title “DBSCAN Revisited: Mis-Claim, Un-
Fixability, and Approximation” that won the conference's best paper award. In this technical …

This textbook explores the different aspects of data mining from the fundamentals to the
complex data types and their applications, capturing the wide diversity of problem domains …

This paper presents a comprehensive study on clustering: exiting methods and
developments made at various times. Clustering is defined as an unsupervised learning …

Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …

Ensemble methods that train multiple learners and then combine them to use, with Boosting
and Bagging as representatives, are well-known machine learning approaches. It has …

The digital world has a wealth of data, such as internet of things (IoT) data, business data,
health data, mobile data, urban data, security data, and many more, in the current age of the …

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …

For many KDD applications, such as detecting criminal activities in E-commerce, finding the
rare instances or the outliers, can be more interesting than finding the common patterns …