Aim of the paper is to illustrate a methodology to implement an ubiquitous city platform called Wi-City provided with centralized and mobile Decision Support Systems (DSSs) that take advantage from all the data of city interest including location, social data and data sensed by monitoring devices. The paper proposes to extend the existing Wi-City DSSs based on location intelligence with an advanced version based on multi criteria customer satisfaction expressed by the users grouped by age where the weights of the criteria are provided by the users instead of expert decision makers, and the rating of the aspects involved in the criteria depends on the evaluation expressed by all the service customers. Including such advanced DSSs in Wi-City makes the platform ready to provide information to users of intelligent cities where recommendations should depend on location and collective intelligence.

Ubiquitous city information platform powered by fuzzy based DSSs to meet multi criteria customer satisfaction: A feasible implementation

GIORDANO, Daniela
2015-01-01

Abstract

Aim of the paper is to illustrate a methodology to implement an ubiquitous city platform called Wi-City provided with centralized and mobile Decision Support Systems (DSSs) that take advantage from all the data of city interest including location, social data and data sensed by monitoring devices. The paper proposes to extend the existing Wi-City DSSs based on location intelligence with an advanced version based on multi criteria customer satisfaction expressed by the users grouped by age where the weights of the criteria are provided by the users instead of expert decision makers, and the rating of the aspects involved in the criteria depends on the evaluation expressed by all the service customers. Including such advanced DSSs in Wi-City makes the platform ready to provide information to users of intelligent cities where recommendations should depend on location and collective intelligence.
2015
978-331925251-3
Computing with words; Mobile information systems; Recommender systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/73207
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