Abstract Recently, Internet of Things (IoT) and multimedia are gaining popularity because of
their usages in various applications. Numerous sensors and automated devices are …

Users of social networking sites often want to manage the sharing of information and content
with different groups of people based on their differing relationships. However, grouping …

This paper proposes an automatic diagnostic method for breast tumour disease using hybrid
Support Vector Machine (SVM) and the Two-Step Clustering Technique. The hybrid …

Neurodegenerative diseases manifest different motor and cognitive signs and symptoms
that are highly heterogeneous. Parsing these heterogeneities may lead to an improved …

Abstract k-means is an effective and efficient clustering algorithm. It uses distance/similarity
metric to find out the distance/similarity among the data objects. The objects which are …

The development of the concept of business intelligence and analysis has emphasized the
importance of the collection, integration, processing of data and reporting of underlying …

The need for smart healthcare tools and techniques has increased due to the availability of
low-cost IoT sensors and devices and the growing aging population in the world. Early …

Hierarchical clustering is a simple and reproducible technique to rearrange data of multiple
variables and sample units and visualize possible groups in the data. Despite the name …

Recent neuroimaging evidence suggests that there might be an anterior-posterior functional
differentiation of the hippocampus along the long-axis. The HERNET (hippocampal …

The process of manually labeling data is very expensive and sometimes infeasible due to
privacy and security issues. This paper investigates the use of two algorithms for clustering …