Determining the number of clusters is an important part of cluster validity that has been
widely studied in cluster analysis. Sum-of-squares based indices show promising properties …

We present two new clustering algorithms called k-sets and k-swaps for data where each
object is a set. First, we define the mean of the sets in a cluster, and the distance between a …

The health sector today contains hidden information that can be important in making
decisions. It is difficult for medical practitioners to predict the disease as it is a complex task …

Semantic clustering of objects such as documents, web sites and movies based on their
keywords is a challenging problem. This requires a similarity measure between two sets of …

Many organizations and individual users are out-sourcing their information which includes
sensitive data into the cloud. To deal with the potential risks of privacy exposure, such data …

According to the CHAOS report from Standish Group during 1992–2017, the degree of
success of projects in the development of software intensive systems (Software Intensive …

Microblogging social media platforms like Twitter, Tumblr and Plurk have radically changed
our lives. The presence of millions of people has made these platforms a preferred channel …

This thesis proposes new approaches to process graph using machine learning algorithms
designed for tabular data. A graph is a data structure made of nodes linked to each others by …

В статье анализируются основные методы и подходы кластерного анализа
семантического ядра с применением методов машинного обучения. Рассматриваются …

Nowadays the majority of tasks in NLP field are solved by means of neural network
language models. These models already have shown state-ofthe-art results in classification …