Existing clustering approaches are usually restricted to crisp clustering, where objects just
belong to one cluster; meanwhile there are some applications where objects could belong to …

Abstract Systems and methods for summarizing online articles for consumption on a user
device are disclosed herein. The system extracts the main body of an article's text from the …

Reducing the effort required by humans in countering malware is of utmost practical value.
We describe a scalable, semi-supervised framework to dig into massive data sets of Android …

Loneliness among college students is an increasingly prevalent issue. While technology-
based methods for detection using behavioural patterns have been proposed, there remains …

Due to increase in traffic in cities and on major roads, it has become a necessity to have an
efficient traffic management system to handle such scenarios. Present traffic management …

Incremental DBSCAN is a one of the density based algorithm to find clusters of arbitrary
shapes. This algorithm is one the method of the DBSCAN algorithm. DBSCAN stands for the …

Density-based spatial clustering of applications with noise (DBSCAN) is a fundament
algorithm for density-based clustering. It can discover clusters of arbitrary shapes and sizes …

Loneliness is a growing health concern as it can lead to depression and other associated
mental health problems for people who experience feelings of loneliness over prolonged …

Spatio-temporal (ST) clustering is a relatively new field in data mining with great popularity,
especially in geographic information. Moving objects are a type of ST data where the …

Cluster analysis, generally known as clustering, is a technique for separating data into
groups (clusters) of similar objects. Except if the system is completely retrained, traditional …