The analysis of news dissemination is of utmost importance since the credibility of
information and the identification of disinformation and misinformation affect society as a …

Over the years, transfer learning has received much attention in machine learning research
and practice. Researchers have found that a major bottleneck associated with machine …

Photos, drawings, figures, etc. supplement textual information in various kinds of media, for
example, in web news or scientific publications. In this respect, the intended effect of an …

The multi-label text categorization is supervised learning, where a document is associated
with multiple labels simultaneously. The current multi-label text categorization approaches …

In recent years, Governments of many countries had promoted higher education in exclusive
areas and disciplines to improve the quality of inhabitant's life, economy, and public …

This paper discusses the problem of marrying structural similarity with semantic relatedness
for Information Extraction from text. Aiming at accurate recognition of relations, we introduce …

In this paper, we study the combination of compression and ℓ 1-norm regularization in a
machine learning context: learning compressible models. By including a compression …

Looking for quality issues in a system can be a very demanding activity. In this article, we
propose an approach based on text mining techniques to quickly identify usability and …

What does a user do when he logs in to the Twitter website? Does he merely browse
through the tweets of all his friends as a source of information for his own tweets, or does he …

Vector space model (VSM) is used in measuring the similarity between documents
according to the frequency of common words among them. Furthermore, the N-gram concept …