Vol-2553⫷ Vol-2554 ⫸Vol-2555
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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