Lukas Lerche
Lukas Lerche
Verified email at tu-dortmund.de - Homepage
Title
Cited by
Cited by
Year
What recommenders recommend–an analysis of accuracy, popularity, and sales diversity effects
D Jannach, L Lerche, F Gedikli, G Bonnin
International conference on user modeling, adaptation, and personalization …, 2013
1032013
What recommenders recommend: an analysis of recommendation biases and possible countermeasures
D Jannach, L Lerche, I Kamehkhosh, M Jugovac
User Modeling and User-Adapted Interaction 25 (5), 427-491, 2015
742015
Adaptation and evaluation of recommendations for short-term shopping goals
D Jannach, L Lerche, M Jugovac
Proceedings of the 9th ACM Conference on Recommender Systems, 211-218, 2015
632015
Using graded implicit feedback for bayesian personalized ranking
L Lerche, D Jannach
Proceedings of the 8th ACM Conference on Recommender systems, 353-356, 2014
562014
Beyond" hitting the hits" Generating coherent music playlist continuations with the right tracks
D Jannach, L Lerche, I Kamehkhosh
Proceedings of the 9th ACM Conference on Recommender Systems, 187-194, 2015
492015
On the value of reminders within e-commerce recommendations
L Lerche, D Jannach, M Ludewig
Proceedings of the 2016 Conference on User Modeling Adaptation and …, 2016
362016
Session-based item recommendation in e-commerce: on short-term intents, reminders, trends and discounts
D Jannach, M Ludewig, L Lerche
User Modeling and User-Adapted Interaction 27 (3-5), 351-392, 2017
312017
Efficient optimization of multiple recommendation quality factors according to individual user tendencies
M Jugovac, D Jannach, L Lerche
Expert Systems with Applications 81, 321-331, 2017
312017
Leveraging multi-dimensional user models for personalized next-track music recommendation
D Jannach, I Kamehkhosh, L Lerche
Proceedings of the Symposium on Applied Computing, 1635-1642, 2017
242017
Recommending based on implicit feedback
D Jannach, L Lerche, M Zanker
Social Information Access, 510-569, 2018
182018
Supporting the design of machine learning workflows with a recommendation system
D Jannach, M Jugovac, L Lerche
ACM Transactions on Interactive Intelligent Systems (TiiS) 6 (1), 1-35, 2016
122016
Item familiarity as a possible confounding factor in user-centric recommender systems evaluation
D Jannach, L Lerche, M Jugovac
icom 14 (1), 29-39, 2015
102015
Adaptive recommendation-based modeling support for data analysis workflows
D Jannach, M Jugovac, L Lerche
Proceedings of the 20th International Conference on Intelligent User …, 2015
82015
Re-ranking recommendations based on predicted short-term interests-a protocol and first experiment
D Jannach, L Lerche, M Gdaniec
Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013
82013
Personalized Next-Track Music Recommendation with Multi-dimensional Long-Term Preference Signals.
I Kamehkhosh, D Jannach, L Lerche
UMAP (Extended Proceedings), 2016
72016
Item Familiarity Effects in User-Centric Evaluations of Recommender Systems.
D Jannach, L Lerche, M Jugovac
RecSys Posters, 2015
52015
Using implicit feedback for recommender systems: characteristics, applications, and challenges
L Lerche
32016
Offline performance vs. subjective quality experience: A case study in video game recommendation
D Jannach, L Lerche
Proceedings of the Symposium on Applied Computing, 1649-1654, 2017
22017
Perspektiven in der Offline-Evaluation von Empfehlungsalgorithmen
D Jannach, L Lerche
HMD Praxis der Wirtschaftsinformatik 50 (5), 34-44, 2013
22013
Empfehlungssysteme, automatische Erzeugung von Wiedergabelisten und Musikdatenbanken
D Jannach, L Lerche, G Bonnin
Handbuch Funktionale Musik, 121-157, 2017
12017
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Articles 1–20