Explore cities all over the world with TourRec!

TourRec suggests unique and personalized tourist trips tailored to your travel interests. Wherever and whenever you want.

Try it out now!

A recommender system for personalized tourist trips

Check out what you can do with TourRec!

Individual Trip Planning

Receive enjoyable routes with the best locations for your next trip!

Personalized Trips

Recommendations are adapted to your interests and context factors such as the weather!

100% Free

TourRec is a research project and completely free of charge!

Worldwide Availability

Tourist trips can be recommended for cities and areas all over the world!

About us

TourRec is developed and provided by a team of researchers and students at the Technical University of Munich (TUM).

Our research focus are Recommender Systems and practical solutions to the Tourist Trip Design Problem.

A selection of our publications in the field of tourist trip recommender systems:
Year Author(s) Title Publicated in Link
2018 D. Herzog, C. Laß, and W. Wörndl TourRec — A Tourist Trip Recommender System for Individuals and Groups Proceedings of the 12th ACM Conference on Recommender Systems (RecSys 2018) Link
2018 D. Herzog, N. Promponas-Kefalas, and W. Wörndl Integrating Public Displays into Tourist Trip Recommender Systems Proceedings of the 3rd Workshop on Recommenders in Tourism co-located with 12th ACM Conference on Recommender Systems (RecSys 2018) PDF
2017 W. Wörndl, A. Hefele and D. Herzog Recommending a Sequence of Interesting Places for Tourist Trips Information Technology & Tourism 17 (1) Link
2017 D. Herzog Recommending a Sequence of Points of Interest to a Group of Users in a Mobile Context Proceedings of the 11th ACM Conference on Recommender Systems (RecSys 2017) Link
2017 C. Laß, D. Herzog and W. Wörndl Context-Aware Tourist Trip Recommendations Proceedings of the 2nd Workshop on Recommenders in Tourism co-located with 11th ACM Conference on Recommender Systems (RecSys 2017) PDF
2016 C. Laß, W. Wörndl and D. Herzog A Multi-tier Web Service and Mobile Client for City Trip Recommendations Proceedings of the 8th EAI International Conference on Mobile Computing, Applications and Services Link
2016 D. Herzog and W. Wörndl Exploiting Item Dependencies to Improve Tourist Trip Recommendations. Proceedings of the Workshop on Recommenders in Tourism co-located with 10th ACM Conference on Recommender Systems (RecSys 2016) PDF

If you have any questions or if you are looking for a research cooperation, please do not hesitate to contact us.