CityRec — A Data-Driven Conversational Destination Recommender System

Authors

  • Saadi Myftija Department of Informatics Technical University of Munich
  • Linus W. Dietz Department of Informatics Technical University of Munich

Keywords:

Tourism recommendation, Conversational recommender systems, Destination characterization

Abstract

In today's age of information, recommender systems have evolved to a must have feature for many platforms, especially in the area of travel and tourism. Destination recommender systems is a challenging domain, since unlike restaurants and points of interests, the items are not so well defined and no reliable rating information is available. Thus, we propose a data-driven characterization of cities, which is then directly used in a conversational recommender system. Through this, we overcome the costly elicitation of expert-based destination characterization, as well as the cold start problem of recommender systems. The recommender system can be used at http://cityrec.cm.in.tum.de/ and the source code has been published.

Author Biographies

Saadi Myftija, Department of Informatics Technical University of Munich

Saadi Myftija completed his Master’s Studies at the Technical University of Munich. His main areas of focus are cloud engineering and backend technologies, but he is also interested in data science and data engineering topics. Currently, he is working as a software engineering consultant at Netlight Consulting.

 

Linus W. Dietz, Department of Informatics Technical University of Munich

Linus W. Dietz is a researcher and doctoral candidate at the Department for Informatics at the Technical University of Munich. His research focuses on tourist recommender systems, data mining, and the analysis of human mobility. He is also an advocate of clean code, which he has recently co-authored a book on (Harrer, Lenhard, & Dietz, 2018).

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Published

2020-01-01

How to Cite

Myftija, S. and Dietz, L. W. (2020) “CityRec — A Data-Driven Conversational Destination Recommender System”, e-Review of Tourism Research, 17(5). Available at: https://journals.tdl.org/ertr/index.php/ertr/article/view/563 (Accessed: 16January2021).

Issue

Section

Demo Papers