Wikipedia is one of the most prominent online platforms from which people acquire
knowledge; thus, its article quality should be of great concern. Currently, many scholars …

Positive-Unlabeled learning (PU learning) is a special case of semi-supervised binary
classification where only a fraction of positive examples is labeled. The challenge is then to …

Article quality has always been a major concern for Wikipedia. To improve article quality, it is
critical to first identify defects. Thus, flaw classification has attracted considerable attention …

In this work, we present the first quality flaw prediction study for articles containing the two
most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any …

Digital libraries and services enable users to access large amounts of data on demand. Yet,
quality assessment of information encountered on the Internet remains an elusive open …

Nowadays, millions of data are generated every day, and their use and interpretation have
become fundamental in all fields. This is particularly true in the area of e-mails classification …

Featured Articles (FA) are considered to be the best articles that Wikipedia has to offer and
in the last years, researchers have found interesting to analyze whether and how they can …

Develo** metrics to estimate the information quality of Wikipedia articles is an interesting
and important research area. In this article, we propose and analyse the feasibility, of a new …

Quality flaws prediction in Wikipedia is an ongoing research trend. In particular, in this work
we tackle the problem of automatically predicting five out of the ten most frequent quality …

Quality flaws prediction in Wikipedia is an ongoing research trend. In particular, in this work
we tackle the problem of automatically assessing the need of including additional citations …