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 …

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

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 …

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 …

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 …

Data analysis plays an indispensable role for understanding various phenomena. Cluster
analysis, primitive exploration with little or no prior knowledge, consists of research …

Cluster analysis is a primary method for database mining. It is either used as a stand-alone
tool to get insight into the distribution of a data set, eg to focus further analysis and data …

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 …