Linus Dietz, M.Sc.
|Phone:||+49 89 289-18676|
|Address:||TUM Institut für Informatik|
Chair of Connected Mobility (I11)
|Consulting hours:||by arrangement|
|Times of absence:||Dec 22 -- Jan 6 2019|
Linus is researcher and PhD student at the Chair of Connected Mobility at the Technical University of Munich (TUM). He holds a M.Sc. in Applied Computer Science from the University of Bamberg.
- Recommender Systems
- Data Analytics
- Software Engineering
- Open Source Software
I'm working on data-driven destination recommender systems. The general scenario is a global planning tool for independent travelers. Initially, I characterize destination regions around the globe along a set of tourism-related dimensions such as typical attractions and costs. In the second step I design algorithms to match the user's preferences and constraints to destinations within the respective query regions.
To achieve these goals, we have recently teamed up with wOndary to evaluate aspects of our research with real travelers.
Current Papers (to appear)
- Beel, J.; Collins, A.; Kopp, O.; Dietz, L. W. & Knoth, P. Mr. DLib’s Scholarly-Recommendation Living-Lab 41st European Conference on Information Retrieval, 2019
- Dietz, L. W., Roy, R., Wörndl, W.: Characterisation of Traveller Types Using Check-in Data from Location-Based Social Networks. In Proceedings of the 26th ENTER2019 eTourism Conference, Springer 2019
- Herzog, D.; Dietz, L. W. & Wörndl, W. Augstein, M.; Herder, E. & Wörndl, W. (Eds.) Tourist Trip Recommendations – Foundations, State of the Art and Challenges. Personalized Human-Computer Interaction, DeGruyter Oldenbourg, 2018
Open thesis topics
Please read through the description and the requirements of the topic carefully if you are interested in one of the topics.
- Currently no topics available!
Book: Java by Comparison
by Simon Harrer, Jörg Lenhard, and Linus Dietz
Published by the Pragmatic Bookshelf
Available at the University Library or the bookstore of your convenience.
Improve your coding skills by comparing your code to that of expert programmers, so you can write code that’s clean, concise, and to the point: code that others will read with pleasure and reuse. Get hands-on advice to level up your coding style through small and understandable examples that compare flawed code to an improved solution. Discover handy tips and tricks, as well as common bugs an experienced Java programmer needs to know. Make your way from a Java novice to a master craftsman.
- Deriving Tourist Mobility Patterns from Check-in Data. Proceedings of the WSDM 2018 Workshop on Learning from User Interactions, 2018 more…
- Teaching Clean Code. Proceedings of the 1st Workshop on Innovative Software Engineering Education, 2018 more…
- Java by Comparison – Become a Java Craftsman in 70 Examples. The Pragmatic Bookshelf, 2018 more…
- Data-Driven Destination Recommender Systems. Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization, ACM, 2018 more…
- Recommending Crowdsourced Trips on wOndary. Proceedings of the RecSys Workshop on Recommenders in Tourism, 2018 more…
- Affective Computing and Bandits: Capturing Context in Cold Start Situations. Proceedings of the RecSys Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, 2018 more…
- Gesellschaft für Informatik (GI) e.V.
- Association for Computing Machinery (ACM)