Digital journalism has faced a dramatic change and media companies are challenged to use
data science algorithms to be more competitive in a Big Data era. While this is a relatively …

News publishers have decreased disseminating news through conventional newspapers
and have migrated to the use of digital means like websites and purpose-built mobile …

More and more people read the news online, eg, by visiting the websites of their favorite
newspapers or by navigating the sites of news aggregators. However, the abundance of …

This paper presents an algorithm audit of the Google Top Stories box, a prominent
component of search engine results and powerful driver of traffic to news publishers. As …

Recommender systems help users deal with information overload by providing tailored item
suggestions to them. The recommendation of news is often considered to be challenging …

User profiling is an important step for solving the problem of personalized news
recommendation. Traditional user profiling techniques often construct profiles of users …

In the recommender systems field, it is increasingly recognized that focusing on accuracy
measures is limiting and misguided. Unsurprisingly, in recent years, the field has witnessed …

The widespread use of temporal aspects in user modeling indicates their importance, and
their consideration showed to be highly effective in various domains related to user …

The present paper introduces and reviews existing technology and research works in the
field of e-Procurement. More specifically this survey aims to collect those relevant …

A personalised news recommendation system extracts news set from multiple press
releases and presents the recommended news to the user. In an effort to build a better …