Among the Web opportunities, e-Commerce processes have increased in relevance requiring the development of complex tools to support all the parties involved therein. This paper proposes a neural network hybrid recommender system able to provide customers, associated with XML-based personal agents within a multi-agent system called MARF, with suggestions about flights purchases. MARF agents continuously monitor customers’ interests and preferences in their commercial Web activities, by constructing and automatically maintaining their profiles. In order to highlight the benefits provided by the proposed flight recommender, some experimental results carried out by exploiting a MARF prototype are presented.
A Neural Network Hybrid Recommender System / Postorino, M; Sarne', G. - 226:(2011), pp. 180-187. (Intervento presentato al convegno Neural Nets WIRN '10 tenutosi a Vietri sul mare (SA) nel 27-29 MAY 2010) [10.3233/978-1-60750-692-8-180].
A Neural Network Hybrid Recommender System
POSTORINO M;SARNE' G
2011-01-01
Abstract
Among the Web opportunities, e-Commerce processes have increased in relevance requiring the development of complex tools to support all the parties involved therein. This paper proposes a neural network hybrid recommender system able to provide customers, associated with XML-based personal agents within a multi-agent system called MARF, with suggestions about flights purchases. MARF agents continuously monitor customers’ interests and preferences in their commercial Web activities, by constructing and automatically maintaining their profiles. In order to highlight the benefits provided by the proposed flight recommender, some experimental results carried out by exploiting a MARF prototype are presented.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
