In the Cultural Heritage domain, the introduction of intelligent systems for planning of cultural visit was very appealing. Indeed when people decide to visit museums or archaeological sites, they usually would like to organize and schedule their time in order to fulfill some requirements and to match, as far as possible, their preferences and needs. In this work, we propose a novel methodology integrating recommendation facilities with agent-based planning techniques in order to implement a planner of routes within cultural sites as museums. In particular, the introduced methodology exploits from one hand a user-centered recommendation strategy to suggest the most suitable cultural items with respect to user's preferences and, from the other one, it leverages multi-agents planning methods to generate the related routes consisting of the sequence of steps necessary to reach precise cultural goals depending on the context, by means of a state space exploration. We present a case of study for the proposed methodology and we describe some experimental results on system efficiency. © 2020
An agent-based approach for recommending cultural tours / Amato, F.; Moscato, Francesco; Moscato, V.; Pascale, F.; Picariello, A.. - In: PATTERN RECOGNITION LETTERS. - ISSN 0167-8655. - 131:(2020), pp. 341-347. [10.1016/j.patrec.2020.01.005]
An agent-based approach for recommending cultural tours
Amato F.;Moscato V.;Picariello A.
2020
Abstract
In the Cultural Heritage domain, the introduction of intelligent systems for planning of cultural visit was very appealing. Indeed when people decide to visit museums or archaeological sites, they usually would like to organize and schedule their time in order to fulfill some requirements and to match, as far as possible, their preferences and needs. In this work, we propose a novel methodology integrating recommendation facilities with agent-based planning techniques in order to implement a planner of routes within cultural sites as museums. In particular, the introduced methodology exploits from one hand a user-centered recommendation strategy to suggest the most suitable cultural items with respect to user's preferences and, from the other one, it leverages multi-agents planning methods to generate the related routes consisting of the sequence of steps necessary to reach precise cultural goals depending on the context, by means of a state space exploration. We present a case of study for the proposed methodology and we describe some experimental results on system efficiency. © 2020File | Dimensione | Formato | |
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