Today’s design of e-services for tourists means dealing with a big quantity of information and metadata that designers should be able to leverage to generate perceived values for users. In this paper we revise the design choices followed to implement a recommender system, highlighting the data processing and architectural point of view, and finally we propose a multi-agent recommender system.

Modeling a multi-agent tourism recommender system / V. Bellandi, P. Ceravolo, E. Tacchini (LECTURE NOTES IN ARTIFICIAL INTELLIGENCE). - In: On the Move to Meaningful Internet Systems: OTM 2019 Conferences / [a cura di] H. Panetto, C. Debruyne, M. Hepp, D. Lewis, C.A. Ardagna, R. Meersman. - [s.l] : Springer, 2019. - ISBN 9783030332457. - pp. 750-757 (( convegno Confederated International Conferences: CoopIS, ODBASE, C&TC tenutosi a Rhodes nel 2019 [10.1007/978-3-030-33246-4_46].

Modeling a multi-agent tourism recommender system

V. Bellandi
;
P. Ceravolo;
2019

Abstract

Today’s design of e-services for tourists means dealing with a big quantity of information and metadata that designers should be able to leverage to generate perceived values for users. In this paper we revise the design choices followed to implement a recommender system, highlighting the data processing and architectural point of view, and finally we propose a multi-agent recommender system.
Recommender system; Big Data
Settore INF/01 - Informatica
2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/713826
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