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 …

The significant growth of interconnected Internet‐of‐Things (IoT) devices, the use of social
networks, along with the evolution of technology in different domains, lead to a rise in the …

In the field of data mining, clustering has shown to be an important technique. Numerous
clustering methods have been devised and put into practice, and most of them locate high …

Abstract Semi-Supervised Graph Clustering (SSGC) has emerged as a pivotal field at the
intersection of graph clustering and semi-supervised learning (SSL), offering innovative …

The objective of this article is to develop a methodology for selecting the appropriate number
of clusters to group and identify human postures using neural networks with unsupervised …

A wireless sensor network (WSN) deploys hundreds or thousands of nodes that may
introduce large-scale data over time. Dealing with such an amount of collected data is a real …

As an unsupervised learning technique, clustering can effectively capture the patterns in a
data stream based on similarities among the data. Traditional data stream clustering …

This paper presents highly robust, novel approaches to solving the forward and inverse
problems of an Electrical Capacitance Tomography (ECT) system for imaging conductive …

The need of fuzzy clustering arises in many real-world applications such as clumping the
users based on their web browsing behavior where the behavior of a user can be similar to …

Purpose: This study aims to analyze and compare the efficiency of tree data structure in data
stream clustering issues. We aim to reveal the efficiency of tree data structures in both …