Publication
Title
News recommender systems : survey and roads ahead
Author
Abstract
More and more people read the news online, e.g., by visiting the websites of their favorite newspapers or by navigating the sites of news aggregators. However, the abundance of news information that is published online every day through different channels can make it challenging for readers to locate the content they are interested in. The goal of News Recommender Systems (NRS) is to make reading suggestions to users in a personalized way. Due to their practical relevance, a variety of technical approaches to build such systems have been proposed over the last two decades. In this work, we review the state-of-the-art of designing and evaluating news recommender systems over the last ten years. One main goal of the work is to analyze which particular challenges of news recommendation (e.g., short item life times and recency aspects) have been well explored and which areas still require more work. Furthermore, in contrast to previous surveys, the paper specifically discusses methodological questions and today's academic practice of evaluating and comparing different algorithmic news recommendation approaches based on accuracy measures.
Language
English
Source (journal)
Information processing and management. - Oxford
Publication
Oxford : 2018
ISSN
0306-4573
Volume/pages
54 :6 (2018) , p. 1203-1227
ISI
000445713800021
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Project info
Foundations of Recommender Systems.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 09.11.2018
Last edited 20.09.2021
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