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Recommender System Model Based on Artificial Immune System (CROSBI ID 520932)

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

Mihaljević, Branko ; Cvitaš, Ana ; Žagar, Mario Recommender System Model Based on Artificial Immune System // Proceedings of the 28th International Conference on Information Technology Interfaces - ITI 2006 / Lužar-Stiffler, Vesna ; Hljuz Dobrić, Vesna (ur.). Zagreb: Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 2006. str. 367-372-x

Podaci o odgovornosti

Mihaljević, Branko ; Cvitaš, Ana ; Žagar, Mario

engleski

Recommender System Model Based on Artificial Immune System

Recommendation and prediction problems mostly rely on recognition and classification tasks. Artificial immune systems, based on natural immunological principles, are computational paradigm for solving such tasks. Additional context dependent response theories like Danger theory explain usage of signaling in recognition process. Recommender system model proposed in this paper addresses construction of a web portal news article recommender based on artificial immune system combined with Danger theory. System knowledge represents learned user preferences using implicit tracking of user actions. System also adapts to evolution of user's opinion and expresses results in personalized recommendation list format.

Artificial Immune System; Danger Theory; Recommender System; RECAIS

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Podaci o prilogu

367-372-x.

2006.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the 28th International Conference on Information Technology Interfaces - ITI 2006

Lužar-Stiffler, Vesna ; Hljuz Dobrić, Vesna

Zagreb: Sveučilišni računski centar Sveučilišta u Zagrebu (Srce)

Podaci o skupu

28th International Conference on Information Technology Interfaces - ITI 2006

predavanje

19.06.2006-22.06.2006

Cavtat, Hrvatska

Povezanost rada

Računarstvo