LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System - Texts

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Research unit

INNOSUISSE

Project number

62368.1 IP-SBM

Project title

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

Texts for this project

	German	French	Italian	English
Short description		-	-
Abstract		-	-	-

Inserted texts

Category	Text
Short description (German)	LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System (Innolink: 101.343 IP-SBM)
Short description (English)	LoCo2: Machine Learning (ML) based Low-CO2/Equivalent-Experience/Equivalent-Cost Tour Booking Recommender System
Abstract (German)	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.