The purpose of this paper is to collate advanced embedding techniques for the classification
of nodes with the help of state-of-art technology named J Deep Learning J, The main …

Most of the real-world networks exhibit community structure, a property that reveals the
existence of natural vertex clusters whose inter-edge density is lower than intra-edge density …

Graphs are considered to be one of the best studied data structures in discrete mathematics
and computer science. Hence, data mining on graphs has become quite popular in the past …

Modelling multiple documents for different applications is a major field of research due to the
tremendous growth in Web data. To find the document similarity, we require clustering to …

This study explores the use of machine learning approaches for fetal health classification
utilizing Cardiotocogram (CTG) data to improve prenatal treatment and maternal-fetal health …

Computing the all pair shortest paths in a graph is a widely used solution, but a time-
consuming process too. The popularly used conventional algorithms rely solely on the …

The study aims to examine the effectiveness of three machine learning algorithms: Random
Forest, Support Vector Machine (SVM), and Logistic Regression, navigating through the …

Water is one of the most indispensable things in our life. However, getting clean drinking
water has become more difficult for a lot of people lately. This research paper uses machine …

Breast cancer remains a significant global health concern around the world, where early and
accurate detection is essential for improving patient outcomes. This work aims to outdo the …

Heart failure is a prevalent cardiovascular disease with significant global mortality rates.
Accurate prediction methods are imperative for predicting cardiovascular disease and …