Purpose Decision support systems developed using machine learning classifiers have
become a valuable tool in predicting various diseases. However, the performance of these …

Pre-clusters assessment is a significant problem in data clustering. It found that visual cluster
tendency assessment (VAT) is majorly focused on addressing the problem of pre-clusters …

Purpose The aim of this study is to propose a deep neural network (DNN) method that uses
side information to improve clustering results for big datasets; also, the authors show that …

Data clustering is the most promising unsupervised technique, and it can be used to partition
the data objects into different clusters. The data objects are placed according to derived …

Nowadays, smartphones, IoT (Internet of Things) devices, and social media produce
massive amounts of data. To control this massive amount of data, we have to arrange the …

Twitter is a popular social network for people to share views or opinions on various topics.
Many people search for health topics through Twitter; thus, obtaining a vast amount of social …

Data mining and big data computing are the emerging domains in the current era of
predictions for societal applications. Millions of people are interested in sharing their views …

For social applications, virtual robotics technologies require the Internet of Things (IoT) and
cloud services. IoT based-speaker identification is required for virtual social robotics to …

Massive information is being created over smartphones, IoT devices, and social media.
Clusters are necessary for managing such unlabeled massive data for organizing the vast …

Forming health tweets clusters is required to give healthcare solutions based on the
assessment of tweets related to diseases and symptoms. As part of this work, existing topic …