Vol-2554
urn:nbn:de:0074-2554-1

Copyright © 2020 for the individual papers by the papers' authors. Copyright © 2020 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

INRA 2019
News Recommendation and Analytics

Proceedings of the 7th International Workshop on News Recommendation and Analytics (INRA 2019)
in conjunction with 13th ACM Conference on Recommender Systems (RecSys 2019)

Copenhagen, Denmark, September 20, 2019.

Edited by

Özlem Özgöbek *
Benjamin Kille **
Jon Atle Gulla *
Andreas Lommatzsch **

* Norwegian University of Science and Technology (NTNU), Department of Computer and Information Science, Trondheim, Norway
** Berlin Institute of Technology, Berlin, Germany

Table of Contents

Preface

Workshop Papers

Public Service Media, Diversity and Algorithmic Recommendation: Tensions between Editorial Principles and Algorithms in European PSM Organizations 6-11
Jannick Kirk Sørensen
Semi-supervised Sentiment Analysis for Under-Resourced Languages with a Sentiment Lexicon 12-17
Peng Liu, Cristina Marco, Jon Atle Gulla
On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems 18-23
Gabriel De Souza P. Moreira, Dietmar Jannach, Adilson Marques Da Cunha
Defining a Meaningful Baseline for News Recommender Systems 24-28
Benjamin Kille, Andreas Lommatzsch
On-the-Fly News Recommendation Using Sequential Patterns 29-34
Mozhgan Karimi, Boris Cule, Bart Goethals
Giveme5W1H: A Universal System for Extracting Main Events from News Articles 35-43
Felix Hamborg, Corinna Breitinger, Bela Gipp
Recommendation Systems for News Articles at the BBC 44-52
Maria Panteli, Alessandro Piscopo, Adam Harland, Jonathan Tutcher, Felix Mercer Moss
Trend-Responsive User Segmentation Enabling Traceable Publishing Insights. A Case Study of a Real-World Large-Scale News Recommendation System 53-62
Joanna Misztal-Radecka, Dominik Rusiecki, Michał Żmuda, Artur Bujak
Enriched Network Embeddings for News Recommendation 63-69
Janu Verma
Leveraging Emotion Features in News Recommendations 70-78
Nastaran Babanejad, Ameeta Agrawal, Heidar Davoudi, Aijun An, Manos Papagelis

2020-02-12: submitted by Özlem Özgöbek, metadata incl. bibliographic data published under Creative Commons CC0
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