LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System (Innolink: 101.343 IP-SBM)

Forschungsstelle

INNOSUISSE

Projektnummer

62368.1 IP-SBM

Projekttitel

LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System (Innolink: 101.343 IP-SBM)

Projekttitel Englisch

LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System (Innolink: 101.343 IP-SBM)

Texte zu diesem Projekt

	Deutsch	Französisch	Italienisch	Englisch
Kurzbeschreibung		-	-
Abstract		-	-	-

Kategorie	Text
Kurzbeschreibung (Deutsch)	LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System (Innolink: 101.343 IP-SBM)
Kurzbeschreibung (Englisch)	LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System
Abstract (Deutsch)	Nezasa offers tour travel booking solutions and thus has a large database of past itineraries available. In this project, a machine learning approach is proposed that will automatically recommend a low CO2 alternative to an individually selected tour, with an equivalent experience score and cost.