An Artificial Immune System Approach to News Article Recommendation (CROSBI ID 507141)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
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
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
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