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An Artificial Immune System Approach to News Article Recommendation (CROSBI ID 507141)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Mihaljević, Branko ; Čavrak, Igor ; Žagar, Mario An Artificial Immune System Approach to News Article Recommendation // Proceedings of the 27th International Conference on INFORMATION TECHNOLOGY INTERFACES, Cavtat, Croatia, June 20-23, 2005 / Lužar-Stiffler, Vesna ; Hljuz Dobrić, Vesna (ur.). Zagreb: Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 2005. str. 411-416-x

Podaci o odgovornosti

Mihaljević, Branko ; Čavrak, Igor ; Žagar, Mario

engleski

An Artificial Immune System Approach to News Article Recommendation

Artificial immune systems are solution finding techniques often used for classification and recommendation problems. Danger theory is one of new context dependant response theories of how an artificial immune system responds to pathogens. News articles recommendation systems solve problems of presenting articles with interesting topics to user honoring evolving user preferences and past choices. This paper describes how artificial immune system with Danger theory can be utilized for news articles recommendation on Web portals or similar media presenter systems and presents algorithm and method for handling user preferences and article features in recommender system.

artificial immune system; Danger theory; recommender system; news article recommendation

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Podaci o prilogu

411-416-x.

2005.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the 27th International Conference on INFORMATION TECHNOLOGY INTERFACES, Cavtat, Croatia, June 20-23, 2005

Lužar-Stiffler, Vesna ; Hljuz Dobrić, Vesna

Zagreb: Sveučilišni računski centar Sveučilišta u Zagrebu (Srce)

Podaci o skupu

27th International Conference on Information Technology Interfaces

predavanje

20.07.2005-23.07.2005

Cavtat, Hrvatska

Povezanost rada

Računarstvo