Towards a Collaborative Repository for the Documentation of Service-Based Antipatterns and Bad Smells. - Justus Bogner; Tobias Boceck; Matthias Popp; Dennis Tschechlov; Stefan Wagner 001; Alfred Zimmermann (ICSA Companion, 2019)

Learning from Past Observations: Meta-Learning for Efficient Clustering Analyses. - Manuel Fritz; Dennis Tschechlov; Holger Schwarz (DaWaK, 2020)

Efficient Exploratory Clustering Analyses with Qualitative Approximations. - Manuel Fritz; Dennis Tschechlov; Holger Schwarz (EDBT, 2021)

AutoML4Clust: Efficient AutoML for Clustering Analyses. - Dennis Tschechlov; Manuel Fritz; Holger Schwarz (EDBT, 2021)

Increasing Explainability of Clustering Results for Domain Experts by Identifying Meaningful Features. - Michael Behringer; Pascal Hirmer; Dennis Tschechlov; Bernhard Mitschang (ICEIS (2), 2022)

Efficient exploratory clustering analyses in large-scale exploration processes. - Manuel Fritz; Michael Behringer; Dennis Tschechlov; Holger Schwarz (VLDB J., 2022)

Approach to Synthetic Data Generation for Imbalanced Multi-class Problems with Heterogeneous Groups. - Dennis Treder-Tschechlov; Peter Reimann 002; Holger Schwarz; Bernhard Mitschang (BTW, 2023)

SDRank: A Deep Learning Approach for Similarity Ranking of Data Sources to Support User-Centric Data Analysis. - Michael Behringer; Dennis Treder-Tschechlov; Julius Voggesberger; Pascal Hirmer; Bernhard Mitschang (ICEIS (1), 2023)

Connecting Domain Experts and Data: Enriching User-Centric Data Analysis with Neural Network-Aided Data Source Suggestion. - Michael Behringer; Dennis Treder-Tschechlov; Julius Voggesberger; Pascal Hirmer; Bernhard Mitschang (ICEIS (Revised Selected Papers 1), 2023)

ML2DAC: Meta-Learning to Democratize AutoML for Clustering Analysis. - Dennis Treder-Tschechlov; Manuel Fritz; Holger Schwarz; Bernhard Mitschang (Proc. ACM Manag. Data, 2023)

Exploiting domain knowledge to address class imbalance and a heterogeneous feature space in multi-class classification. - Vitali Hirsch; Peter Reimann 002; Dennis Treder-Tschechlov; Holger Schwarz; Bernhard Mitschang (VLDB J., 2023)

Empowering Domain Experts to Enhance Clustering Results Through Interactive Refinement. - Michael Behringer; Dennis Treder-Tschechlov; Jannis Rapp (DASFAA (7), 2024)

Ensemble Clustering based on Meta-Learning and Hyperparameter Optimization. - Dennis Treder-Tschechlov; Manuel Fritz; Holger Schwarz; Bernhard Mitschang (Proc. VLDB Endow., 2024)