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Authors: Özlem Özgöbek 1 ; Jon Atle Gulla 2 and R. Cenk Erdur 3

Affiliations: 1 NTNU and Ege University, Norway ; 2 NTNU, Norway ; 3 Ege University, Turkey

ISBN: 978-989-758-106-9

Keyword(s): Recommender Systems, News Source, News Recommendation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Recommendation Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Software Agents and Internet Computing

Abstract: Recommender systems aim to deliver the most suitable item to the user without the manual effort of the user. It is possible to see the applications of recommender systems in a lot of different domains like music, movies, shopping and news. Recommender system development have many challenges. But the dynamic and diverse environment of news domain makes news recommender systems a little bit more challenging than other domains. During the recommendation process of news articles, personalization and analysis of news content plays an important role. But beyond recommending the articles itself, we think that where the news come from is also very important. Different news sources have their own style, view and way of expression and they may give the user a complete, balanced and wide perspective of news stories. In this paper we explain the need for including news sources in news recommendation and propose a news source recommendation method by finding out the implicit relations and similari ties between news sources by using semantics and association rules. (More)

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Paper citation in several formats:
Özgöbek, Ö.; Gulla, J. and Erdur, R. (2015). Recommending Sources in News Recommender Systems.In Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-106-9, pages 526-532. DOI: 10.5220/0005489205260532

@conference{webist15,
author={Özlem Özgöbek. and Jon Atle Gulla. and R. Cenk Erdur.},
title={Recommending Sources in News Recommender Systems},
booktitle={Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2015},
pages={526-532},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005489205260532},
isbn={978-989-758-106-9},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Recommending Sources in News Recommender Systems
SN - 978-989-758-106-9
AU - Özgöbek, Ö.
AU - Gulla, J.
AU - Erdur, R.
PY - 2015
SP - 526
EP - 532
DO - 10.5220/0005489205260532

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