The clustering problem has been considered one of the most relevant problems in the
research area of unsupervised learning. However, the comprehension and definition of such …

Students' academic achievement is largely driven by their social phenomena, which is
shaped by social influence and opinion dynamics. In this paper, we employed a machine …

Sentiment analysis is the process of predicting the sentiment polarity of review data based
on a given data set. Huge amount of review data is generated in each day on the Web. This …

The aim of this article is to determine the socioeconomic level (SEL) with disaggregation of
the Basic Statistical Area (BSA) in the Mexican Republic. The methodology used is the one …

Document collections can be characterised in a variety of ways. Two key approaches are
clustering, which partitions collections into subcollections with the expectation that the …

Abstract Machine learning is a suitable pattern recognition technique for detecting
correlations between data. In the case of unsupervised learning, the groups formed from …

Cluster labelling is a technique which provides useful information about the cluster to the
end users. In this paper, we propose a novel approach which is the follow-up of our previous …

Clustering algorithms are often used to form groups based on the similarity of their members.
In this context, understanding a group is just as important as its composition. Identifying, or …

The clustering problem has been considered one of the most relevant problems in the
research area of unsupervised learning. However, the comprehension and definition of such …

Abstract Cluster Labeling Models apply Artificial Intelligence techniques to extract the key
features of clustered data to provide a tool for clustering interpretation. For this purpose, we …