Naslov
An Artificial Immune System Approach to News Article Recommendation

Autori
Mihaljević, Branko ; Čavrak, Igor ; Žagar, Mario

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
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), 2005, 411-416

Skup
27th International Conference on Information Technology Interfaces

Mjesto i datum
Cavtat, Hrvatska, 20.06.2005. - 23.06.2005

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

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

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA