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Authors: Servet Tasci and Ilyas Cicekli

Affiliation: Hacettepe University, Turkey

Keyword(s): Recommendation Systems, Content-based Filtering, Text Summarization, Text Classification.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems ; User Profiling and Recommender Systems

Abstract: Nowadays, the amount of documents on internet resources is increasing at an unprecedented speed and users are tired of searching important and related ones among enormous amount of documents. Users require a personalized support in sifting through large amounts of available information according to their interests and recommendation systems try to answer this need. In this context, it is crucial to offer user friendly tools that facilitate faster and more accurate access to articles in digital newspapers. In this paper, a time-based recommendation system for news domain is presented. News articles are recommended according to user dynamic and static profiles. User dynamic profiles reflect user past interests and recent interests play much bigger roles in the selection of recommendations. Our recommendation system is a complete content-based recommendation system together with categorization, summarization and news collection modules.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Tasci, S. and Cicekli, I. (2014). A Media Tracking and News Recommendation System. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR; ISBN 978-989-758-048-2; ISSN 2184-3228, SciTePress, pages 53-60. DOI: 10.5220/0005072000530060

@conference{kdir14,
author={Servet Tasci. and Ilyas Cicekli.},
title={A Media Tracking and News Recommendation System},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR},
year={2014},
pages={53-60},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005072000530060},
isbn={978-989-758-048-2},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2014) - KDIR
TI - A Media Tracking and News Recommendation System
SN - 978-989-758-048-2
IS - 2184-3228
AU - Tasci, S.
AU - Cicekli, I.
PY - 2014
SP - 53
EP - 60
DO - 10.5220/0005072000530060
PB - SciTePress

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