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Titel:

Data-Driven Destination Recommender Systems

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Linus W. Dietz
Abstract:
Given endless possibilities to travel around the world, it has become challenging to choose where to travel to. We argue that traditional media is insufficient to make informed decisions where to travel to, because of lacking objectivity, comparability and being out-of-date. Thus, travel planning is an interesting field to establish data-driven recommender systems that support users to master information explosion. We present working packages for a doctorate project that brings together the fiel...     »
Kongress- / Buchtitel:
Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization
Ausrichter der Konferenz:
ACM
Verlag / Institution:
ACM
Verlagsort:
New York, NY, USA
Jahr:
2018
Jahr / Monat:
2018-07
Seiten:
4
Reviewed:
ja
Volltext / DOI:
doi:10.1145/3209219.3213591
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