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
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.
978-1-60750-691-1
Multi-agent system; Neural network; Recommender system
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/17072
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