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Authors: Giovanni Giuffrida 1 and Calogero G. Zarba 2

Affiliations: 1 University of Catania, Italy ; 2 Neodata Intelligence s.r.l., Italy

Keyword(s): Recommender systems, Text mining, Data mining.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Industrial Applications of AI ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: We present a recommendation algorithm for online news based on collective intelligence and content. When a user asks for personalized news, our algorithm recommends news articles that (i) are popular among the members of the online community (the collective intelligence part), and (ii) are similar in content to the news articles the user has read in the past (the content part). Our algorithm computes its recomendations based on the collective behavior of the online users, as well as on the feedback the users provide to the algorithm’s recommendations. The users’ feedback can moreover be used to measure the effectiveness of our recomendation algorithm in terms of the information retrieval concepts of precision and recall. The cornerstone of our recommendation algorithm is a basic relevance algorithm that computes how relevant a news article is to a given user. This basic relevance algorithm can be optimized in order to obtain a faster online response at the cost of minimal offline com putations. Moreover, it can be turned into an approximated algorithm for an even faster online response. (More)

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Paper citation in several formats:
Giuffrida, G. and G. Zarba, C. (2011). A RECOMMENDATION ALGORITHM FOR PERSONALIZED ONLINE NEWS BASED ON COLLECTIVE INTELLIGENCE AND CONTENT. In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-8425-40-9; ISSN 2184-433X, SciTePress, pages 189-194. DOI: 10.5220/0003115401890194

@conference{icaart11,
author={Giovanni Giuffrida. and Calogero {G. Zarba}.},
title={A RECOMMENDATION ALGORITHM FOR PERSONALIZED ONLINE NEWS BASED ON COLLECTIVE INTELLIGENCE AND CONTENT},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2011},
pages={189-194},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003115401890194},
isbn={978-989-8425-40-9},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - A RECOMMENDATION ALGORITHM FOR PERSONALIZED ONLINE NEWS BASED ON COLLECTIVE INTELLIGENCE AND CONTENT
SN - 978-989-8425-40-9
IS - 2184-433X
AU - Giuffrida, G.
AU - G. Zarba, C.
PY - 2011
SP - 189
EP - 194
DO - 10.5220/0003115401890194
PB - SciTePress

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