Data mining is an analytical approach that contributes to achieving a solution to many
problems by extracting previously unknown, fascinating, nontrivial, and potentially valuable …

The knowledge gained from data mining is highly dependent on the experience of an expert
for further analysis to increase effectiveness and wise decision-making. This mined …

This study investigated the similarity of the catchments with the k-means clustering method
by using the hydrological response unit (HRU) images of 33 catchments located in the …

Minibus taxi public transport is a seemingly chaotic phenomenon in the developing cities of
the Global South with unique mobility and operational characteristics. Eventually this …

In unsupervised learning tasks, one of the most significant and challenging aspects is how to
estimate the optimal number of clusters (NC) for a particular set of data. Identifying NC in a …

Social media have become very popular as the number of users, organizations and
research associated continue to increase rapidly. As such, user profiling becomes prominent …

The goal of current research is to compare the data clustering techniques and cluster validity
indices for geometrical feature extraction using point cloud. Here, the point clouds are …

Clustering analysis is a significant technique in various fields, including unsupervised
machine learning, data mining, pattern recognition, and image analysis. Many clustering …

Background The choice of an appropriate similarity measure plays a pivotal role in the
effectiveness of clustering algorithms. However, many conventional measures rely solely on …