Publications

Mathias Jesse, Christine Bauer, Dietmar Jannach: Intra-list similarity and human diversity perceptions of recommendations: the details matter. User Modeling and User-Adapted Interaction, Springer Verlag GmbH, Berlin, Heidelberg, New York, 2022,

Ahtsham Manzoor, Dietmar Jannach: INFACT: An Online Human Evaluation Framework forConversational Recommendation. Proceedings of the Fourth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS 2022), CEUR Workshop Proceedings (CEUR-WS.org), 3294, Aachen, 2022, S. 6 - 11.

Ahtsham Manzoor, Dietmar Jannach: INSPIRED2: An Improved Dataset for Sociable Conversational Recommendation. Proceedings of the Fourth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS 2022), CEUR Workshop Proceedings (CEUR-WS.org), 3294, Aachen, 2022, S. 73 - 80.

Nicole Burgstaller, Claudia van der Rijst, Nina Angela Lobnig, Claudia Steinberger: Learn to query databases in an interactive and engaging way. Local Proceedings of the 15th International Conference on Informatics in Schools, 2022, S. 129 - 130.

Dietmar Jannach: Multi-Objective Recommender Systems: Survey and Challenges. 2nd Workshop on Multi-Objective Recommender Systems (MORS 2022), CEUR Workshop Proceedings (CEUR-WS.org), 3268, Aachen, 2022, S. 1 - 11.

Koby Bibas, Oren Sar Shalom, Dietmar Jannach: Collaborative Image Understanding. CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Association for Computing Machinery (ACM), New York, 2022, S. 77 - 87.

Sara Latifi Alavijeh, Dietmar Jannach: Streaming Session-Based Recommendation: When Graph Neural Networks meet the Neighborhood. RecSys '22: Proceedings of the 16th ACM Conference on Recommender Systems, Association for Computing Machinery (ACM), New York, 2022, S. 420 - 426.

Patrick Rodler: How should I compute my candidates? A taxonomy and classification of diagnosis computation algorithms. 33rd International Workshop on Principle of Diagnosis – DX 2022, LAAS-CNRS-ANITI, 2022, S. 1 - 9.

Tommaso Di Noia, Francesco Maria Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo: Conversational recommendation: Theoretical model and complexity analysis. Information Sciences, Elsevier Ltd., 614, Oxford, 2022, S. 325 - 347.

Sara Latifi, Dietmar Jannach, Andres Ferraro: Sequential recommendation: A study on transformers, nearest neighbors and sampled metrics. Information Sciences, Elsevier Ltd., 609, Oxford, 2022, S. 660 - 678.

Dietmar Jannach: Evaluating conversational recommender systems. Artificial Intelligence Review, Springer, Berlin, 2022,

Veronika Bogina, Tsvi Kuflik, Dietmar Jannach, Maria Bielikova, Michal Kompan, Christoph Trattner: Considering temporal aspects in recommender systems: a survey. User Modeling and User-Adapted Interaction, Springer Verlag GmbH, Berlin, Heidelberg, New York, 2022,

Sagi Eden, Amit Livne, Oren Sar Shalom, Bracha Shapira, Dietmar Jannach: Investigating the value of subtitles for improved movie recommendations. UMAP '22: Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery (ACM), New York, 2022, S. 99 - 109.

V.W. Anelli, Alejandro Bellogin, T. Di Noia, Dietmar Jannach, Claudio Pomo: Top-N Recommendation Algorithms: A Quest for the State-of-the-Art. UMAP '22: Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery (ACM), New York, 2022, S. 121 - 131.

Ahtsham Manzoor, Dietmar Jannach: Revisiting Retrieval-based Approaches for Conversational Recommender Systems. IIR 2022: 12th Italian Information Retrieval Workshop, CEUR Workshop Proceedings (CEUR-WS.org), Aachen, 2022, S. 1 - 6.

Patrick Rodler: Random vs. Best-First: Impact of Sampling Strategies on Decision Making in Model-Based Diagnosis. Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI Press, 36, Menlo Park (CA), 2022, S. 5869 - 5878.

Dietmar Jannach, Li Chen: Conversational Recommendation: A Grand AI Challenge. AI Magazine, AAAI Press, 43, Menlo Park (CA), 2022, S. 151 - 163.

Anastasiia Klimashevskaia, Mehdi Elahi, Dietmar Jannach, Christoph Trattner, Lars Skjaerven: Mitigating Popularity Bias in Recommendation: Potential and Limits of Calibration Approaches. BIAS 2022: Advances in Bias and Fairness in Information Retrieval, Springer, Cham, 1610, 2022, S. 82 - 90.

Dietmar Jannach, Pearl Pu, Francesco Ricci, Markus Zanker: Recommender Systems: Frontiers and Trends. AI Magazine, AAAI Press, 43, Menlo Park (CA), 2022, S. 145 - 150.

Ahtsham Manzoor, Dietmar Jannach: Towards retrieval-based conversational recommendation. Information Systems, Elsevier, 109, 2022, S. 1 - 14.

Patrick Rodler: One step at a time: An efficient approach to query-based ontology debugging. Knowledge-Based Systems, Elsevier, 251, 2022, S. 1 - 30.

Patrick Rodler: A formal proof and simple explanation of the QuickXplain algorithm. Artificial Intelligence Review, Springer, 55, Berlin, 2022, S. 6185 - 6206.

Ralf Laue, Heinrich C. Mayr, Bernhard Thalheim: 100 Years of Graphical Business Process Modelling. Enterprise Modelling and Information Systems Architectures, 17, 2022, S. 1 - 5.

Patrick Rodler: Memory-limited model-based diagnosis. Artificial Intelligence, 305, 2022, S. 1 - 36.

Christoph Trattner, Dietmar Jannach, Enrico Motta, Irene Costera Meijer, Nicholas Diakopoulos, Mehdi Elahi, Andreas L. Opdahl, Bjørnar Tessem, Njål Borch, Morten Fjeld, Lilja Øvrelid, Koenraad De Smedt, Hallvard Moe: Responsible media technology and AI: challenges and research directions. AI and Ethics, Springer Nature Switzerland AG, 2021, S. 1 - 10.

Paolo Cremonesi, Dietmar Jannach: Progress in recommender systems research: Crisis? What crisis?. AI Magazine, AAAI Press, 42, Menlo Park (CA), 2021, S. 43 - 54.

Dietmar Jannach, Pearl Pu, Francesco Ricci, Markus Zanker: Recommender Systems: Past, Present, Future. AI Magazine, AAAI Press, 42, Menlo Park (CA), 2021, S. 3 - 6.

Patrick Rodler, Erich Christian Teppan, Dietmar Jannach: Randomized Problem-Relaxation Solving for Over-Constrained Schedules. Proceedings of the 18th International Conference on Principles of Knowledge Representation and Reasoning , IJCAI Inc., Menlo Park (CA), 2021, S. 696 - 701.

Mehdi Elahi, Dietmar Jannach, Lars Skjaerven, Erik Knudsen, Helle Sjøvaag, Kristian Tolonen, Øyvind Holmstad, Igor Pipkin, Eivind Throndsen, Agnes Stenbom, Eivind Fiskerud, Adrian Oesch, Loek Vredenberg, Christoph Trattner: Towards responsible media recommendation. AI and Ethics, Springer Nature Switzerland AG, 2021, S. 1 - 12.

Adil Mukhtar, Birgit Hofer, Dietmar Jannach, Gerhard Wotowa: Spreadsheet Debugging: The Perils of Tool Over-Reliance. Journal of Systems and Software, Elsevier Ltd., 184, Oxford, 2021, S. 1 - 16.

Volodymyr Shekhovtsov, Claudia Steinberger, Christian Kop: Model Based Coupling of Context Aware Middleware and Ambient Assisted Healthcare Systems. ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS 2021 Companion, IEEE, Piscataway (NJ), 2021, S. 188 - 196.

Fatih Gedikli, Anne Stockem Novo, Dietmar Jannach: Automated Identification of News Story Chains: A New Dataset and Entity-based Labeling Method. 9th International Workshop on News Recommendation and Analytics (INRA 2021), CEUR Workshop Proceedings (CEUR-WS.org), Aachen, 2021, S. 1 - 14.

Ahtsham Manzoor, Dietmar Jannach: Generation-based vs. Retrieval-based Conversational Recommendation: A User-Centric Comparison. RecSys '21: Fifteenth ACM Conference on Recommender Systems, Association for Computing Machinery (ACM), New York, 2021, S. 515 - 520.

Ahtsham Manzoor, Dietmar Jannach: Conversational recommendation based on end-to-end learning: How far are we?. Computers in Human Behavior Reports, Elsevier, 4, 2021, S. 1 - 9.

Sara Latifi Alavijeh, Noemi Mauro, Dietmar Jannach: Session-aware Recommendation: A Surprising Quest for the State-of-the-art. Information Sciences, Elsevier Ltd., 573, Oxford, 2021, S. 291 - 315.

Gediminas Adomavicius, Dietmar Jannach, Stephan Leitner, Jingjing Zhang: Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation. Workshop on Simulation Methods for Recommender Systems (SimuRec) at ACM RecSys ’21, arXiv.org, Ithaca, NY, 2021, S. 1 - 4.

Patrick Rodler: Linear-Space Best-First Diagnosis Search. Proceedings of the Fourteenth International Symposium on Combinatorial Search (SoCS 2021), AAAI Press, Menlo Park (CA), 2021, S. 188 - 190.

Mathias Jesse, Dietmar Jannach: Digital Nudging with Recommender Systems: Survey and Future Directions. Computers in Human Behavior Reports, Elsevier, 3, 2021, S. 1 - 14.

Karin Maria Hodnigg, Christian Macho, Martin Pinzger, Dietmar Jannach: Comprehending Spreadsheets: Which Strategies do Users Apply?. Proceedings of the 29th IEEE/ACM International Conference on Program Comprehension, IEEE, Piscataway (NJ), 2021, S. 386 - 390.

Dietmar Jannach, Mathias Jesse, Michael Jugovac, Christoph Trattner: Exploring Multi-List User Interfaces for Similar-Item Recommendations. UMAP '21: Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery (ACM), New York, 2021, S. 224 - 228.

Konstantin Schekotihin, Birgit Hofer, Franz Wotawa, Dietmar Jannach: AI-based Spreadsheet Debugging. Artificial Intelligence Methods for Software Engineering, World Scientific Publishing, Singapore, 2021, S. 371 - 399.

Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, Li Chen: A Survey on Conversational Recommender Systems. ACM Computing Surveys, Association for Computing Machinery (ACM), 54, New York, 2021, S. 1 - 36.

Josef Bauer, Dietmar Jannach: Improved Customer Lifetime Value Prediction with Sequence-To-Sequence Learning and Feature-based Models. ACM Transactions on Knowledge Discovery from Data, Association for Computing Machinery (ACM), 15, New York, 2021, S. 1 - 37.

Birgit Hofer, Dietmar Jannach, Patrick Koch, Konstantin Schekotihin, Franz Wotawa: Product Metrics for Spreadsheets - A Systematic Review. Journal of Systems and Software, Elsevier Ltd., 175, Oxford, 2021, S. 1 - 18.

Rami Cohen, Oren Sar Shalom, Dietmar Jannach, Amihood Amir: A Black-Box Attack Model for Visually-Aware Recommenders. WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining, Association for Computing Machinery (ACM), New York, 2021, S. 94 - 102.

Dietmar Jannach, Christine Bauer: Escaping the McNamara Fallacy: Towards more Impactful Recommender Systems Research. AI Magazine, AAAI Press, 41, Menlo Park (CA), 2021, S. 79 - 95.

Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach: A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research. ACM Transactions on Information Systems, Association for Computing Machinery (ACM), 39, New York, 2021, S. 1 - 49.

Patrick Rodler: DynamicHS: Streamlining Reiter's Hitting-Set Tree for Sequential Diagnosis. http://arxiv.org/, 2020,

Christian Kop: Analyzing Model Element Labels of Business Process Model Examples Provided on the Web. eKNOW 2020, The Twelfth International Conference on Information, Process, and Knowledge Management, International Academy, Research, and Industry Association (IARIA), 2020, S. 43 - 48.

Maurizio Ferrari Dacrema, Federico Parroni, Paolo Cremonesi, Dietmar Jannach: Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems. CIKM ’20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, ACM Digital Library, New York, NY, 2020, S. 355 - 363.

Malte Ludewig, Noemi Mauro, Sara Latifi Alavijeh, Dietmar Jannach: Empirical Analysis of Session-Based Recommendation Algorithms. User Modeling and User-Adapted Interaction, Springer Netherlands, Dordrecht, 2020, S. 1 - 33.

Patrick Rodler: Memory-Limited Model-Based Diagnosis. http://arxiv.org/, 2020,

Toine Bogers, Marijn Koolen, Casper Petersen, Bamshad Mobasher, Alexander Tuzhilin, Oren Sar Shalom, Dietmar Jannach, Joseph A. Konstan: ComplexRec-ImpactRS 2020: Recommendation in Complex Scenarios and the Impact of Recommender Systems 2020. CEUR Workshop Proceedings (CEUR-WS.org), Aachen, 2020,

Patrick Rodler, Fatima Elichanova: Do We Really Sample Right In Model-Based Diagnosis? . DX-2020 Conference Proceedings, 2020, S. 1 - 8.

Patrick Rodler: DynamicHS: Optimizing Reiter’s HS-Tree for Sequential Diagnosis. DX-2020 Conference Proceedings, 2020, S. 1 - 8.

Dietmar Jannach, Ahtsham Manzoor: End-to-End Learning for Conversational Recommendation: A Long Way to Go?. Proceedings of the 7th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 14th ACM Conference on Recommender Systems (RecSys 2020), 2020, S. 72 - 76.

Andres Ferraro, Dietmar Jannach, Xavier Serra: Exploring Longitudinal Effects of Session-based Recommendations. RecSys '20: Fourteenth ACM Conference on Recommender Systems, ACM Digital Library, New York, NY, 2020, S. 474 - 479.

Patrick Rodler: Reuse, Reduce and Recycle: Optimizing Reiter's HS-Tree for Sequential Diagnosis. 24th European Conference on Artificial Intelligence - ECAI 2020, IOS Press, 325, Amsterdam, 2020, S. 873 - 880.

Patrick Rodler: Sound, Complete, Linear-Space, Best-First Diagnosis Search. DX-2020 Conference Proceedings, 2020, S. 1 - 8.

Patrick Rodler, Erich Christian Teppan: The Scheduling Job-Set Optimization Problem: A Model-Based Diagnosis Approach. DX-2020 Conference Proceedings, 2020, S. 1 - 8.

Dietmar Jannach, Gabriel de Souza P. Moreira, Even Oldridge: Why Are Deep Learning Models Not Consistently Winning Recommender Systems Competitions Yet?. RecSysChallenge '20: Proceedings of the Recommender Systems Challenge 2020, ACM Digital Library, New York, NY, 2020, S. 44 - 49.

Dietmar Jannach, Bamshad Mobasher, Shlomo Berkovsky: Research directions in session-based and sequential recommendation. User Modeling and User-Adapted Interaction, Springer Netherlands, 30, Dordrecht, 2020, S. 609 - 616.

Dietmar Jannach, Bamshad Mobasher, Shlomo Berkovsky: User Modeling and User-Adapted Interaction, Special Issue on Recommender Systems based on Session-based and Sequential Recommender Systems. Springer Netherlands, 30, Dordrecht, 2020,

Dietmar Jannach, Surya Kallumadi, Tracy Holloway King, Luo Weihua, Shervin Malmasi: Proceedings of the SIGIR eCom Workshop 2020. 2020,

Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach: Methodological Issues in Recommender Systems Research. Proceedings of the 2020 International Joint Conference on Artificial Intelligence (IJCAI-PRICAI 2020), International Joint Conferences on Artificial Intelligence, 2020, S. 4706 - 4710.

Patrick Rodler: Too Good to Throw Away: A Powerful Reuse Strategy for Reiter's Hitting Set Tree. Proceedings of the Thirteenth International Symposium on Combinatorial Search, SOCS 2020, AAAI Press, Menlo Park (CA), 2020, S. 135 - 136.

Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha: Hybrid Session-based News Recommendation using Recurrent Neural Networks. Proceedings of the LatinX in AI Research (LXAI) at ICML 20, 2020, S. 1 - 3.

Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Pizzato: Multistakeholder Recommendation: Survey and Research Directions. User Modeling and User-Adapted Interaction, Springer Netherlands, 30, Dordrecht, 2020, S. 127 - 158.

Patrick Rodler: On Expert Behaviors and Question Types for Efficient Query-Based Ontology Fault Localization. http://arxiv.org/, 2020,

Patrick Rodler: Understanding the QuickXPlain Algorithm: Simple Explanation and Formal Proof. http://arxiv.org/, 2020,

Dietmar Jannach, Michael Jugovac: Measuring the Business Value of Recommender Systems. ACM Transactions on Management Information Systems (TMIS), Association for Computing Machinery (ACM), 10, New York, 2019, S. 1 - 23.

Claudia Steinberger, Joachim Frießer: SEMANTICAL ENRICHMENT OF WEB USER INTERFACES IN THE CROWD. IADIS International Journal on WWW/Internet, International Association for Development of the Information Society (IADIS), 17, Lisbon, 2019, S. 56 - 70.

Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha: Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks. IEEE Access, IEEE, 7, Piscataway (NJ), 2019, S. 169185 - 169203.

Claudia Steinberger, Joachim Frießer: Why and How to Capture the Semantics of Web User Interfaces. 18th International Conference on WWW/INTERNET 2019, International Association for Development of the Information Society (IADIS), Lisbon, 2019, S. 35 - 42.

Patrick Rodler, Michael Eichholzer: On the Usefulness of Different Expert Question Types for Fault Localization in Ontologies. 30th Int’l Workshop on Principles of Diagnosis (DX’19), 2019, S. 1 - 8.

Patrick Rodler: Reuse, Reduce and Recycle: Adapting Reiter’s HS-Tree to Sequential Diagnosis. 30th Int’l Workshop on Principles of Diagnosis (DX’19), 2019, S. 1 - 8.

Patrick Koch, Konstantin Schekotihin, Dietmar Jannach, Birgit Gertraud Hofer, Franz Wotawa: Metric-based Fault Prediction for Spreadsheets. IEEE Transactions on Software Engineering, IEEE, 2019,

Oren Sar Shalom, Dietmar Jannach, Ido Guy: Proceedings of the 1st Workshop on the Impact of Recommender Systemsco-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019). CEUR Workshop Proceedings (CEUR-WS.org), Aachen, 2019,

Christoph Trattner, Dietmar Jannach: Learning to Recommend Similar Items from Human Judgements. User Modeling and User-Adapted Interaction, Springer Verlag GmbH, Berlin, Heidelberg, New York, 2019, S. 1 - 49.

Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach: Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches. RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems, Association for Computing Machinery (ACM), New York, 2019, S. 101 - 109.

Dietmar Jannach, Michael Jugovac, Ingrid Nunes: Explanations and User Control in Recommender Systems. Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond - ABIS 2019, Association for Computing Machinery (ACM), New York, 2019, S. 31

Dietmar Jannach, Michael Jugovac, Ingrid Nunes: Explanations and User Control in Recommender Systems. Personalized Human-Computer Interaction, De Gruyter, Berlin/Boston, 2019, S. 133 - 156.

Patrick Rodler, Michael Eichholzer: How You Ask Matters: A Simple Expert Questioning Approach for Efficient Ontology Fault Localization. CEUR Workshop Proceedings, CEUR Workshop Proceedings (CEUR-WS.org), 2518, Aachen, 2019,

Malte Ludewig, Dietmar Jannach: Learning to rank hotels for search and recommendation from session-based interaction logs and meta data. RecSys Challenge '19: Proceedings of the Workshop on ACM Recommender Systems Challenge, Association for Computing Machinery (ACM), 2019, S. 1 - 5.

Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha: On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems. 9th International Workshop on News Recommendation and Analytics (INRA 2019), CEUR Workshop Proceedings (CEUR-WS.org), Aachen, 2019,

Malte Ludewig, Noemi Mauro, Sara Latifi Alavijeh, Dietmar Jannach: Performance Comparison of Neural and Non-Neural Approaches to Session-based Recommendation. RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems, Association for Computing Machinery (ACM), New York, 2019, S. 426 - 466.

Dietmar Jannach, Oren Sar Shalom, Joseph A. Konstan: Towards More Impactful Recommender Systems Research. Proceedings of the 1st Workshop on the Impact of Recommender Systemsco-located with 13th ACM Conference on Recommender Systems (ACM RecSys 2019), CEUR Workshop Proceedings (CEUR-WS.org), Aachen, 2019,

Malte Ludewig, Dietmar Jannach: User-Centric Evaluation of Session-Based Recommendations for an Automated Radio Station. RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems, Association for Computing Machinery (ACM), New York, 2019, S. 516 - 520.

Claudia Steinberger, Judith Michael: Using Semantic Markup to Boost Context Awareness for Assistive Systems. Smart Assisted Living, Springer, Berlin, 2019, S. 227 - 246.

Patrick Rodler: Towards Optimizing Reiter's HS-Tree for Sequential Diagnosis. http://arxiv.org/, 2019,

Patrick Rodler, Michael Eichholzer: On the Usefulness of Different Expert Question Types for Fault Localization in Ontologies. Advances and Trends in Artificial Intelligence. From Theory to Practice, Springer, 11606, Berlin, 2019, S. 360 - 375.

Markus Zanker, Laurens Rook, Dietmar Jannach: Measuring the Impact of Online Personalisation: Past, Present and Future. International Journal of Human-Computer Studies, Academic Press / Elsevier, 131, Oxford, 2019, S. 160 - 168.

George Angelos Papadopoulos, George Samaras, Stephan Weibelzahl, Dietmar Jannach, Olga C. Santos: ACM UMAP’19 Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization . ACM - New York, New York, NY, 2019,

Iman Kamehkhosh, Geoffray Bonnin, Dietmar Jannach: Effects of Recommendations on the Playlist Creation Behavior of Users. User Modeling and User-Adapted Interaction, Springer Verlag GmbH, Berlin, Heidelberg, New York, 2019, S. 1 - 38.

Dietmar Jannach, Konstantin Schekotihin, Philipp Fleiß, Patrick Rodler: Are Query-Based Ontology Debuggers Really Helping Knowledge Engineers?. Knowledge-Based Systems, Elsevier, 179, 2019, S. 92 - 107.

Pasquale Lops, Dietmar Jannach, Cataldo Musto, Toine Bogers, Marijn Koolen: User Modeling and User-Adapted Interaction (UMUAI). Springer Nature, 6, Berlin und London, 2019,

Christian Kop: 43. WI-MAW-Rundbrief (Gesellschaft für Informatik GI). Köllen Druck+Verlag GmbH, 25, Bonn, 2019,

Patrick Rodler, Michael Eichholzer: A New Expert Questioning Approach to More Efficient Fault Localization in Ontologies. http://arxiv.org/, 2019,

Pasquale Lops, Dietmar Jannach, Cataldo Musto, Toine Bogers, Marijn Koolen: Trends in content-based recommendation. User Modeling and User-Adapted Interaction, Springer Verlag GmbH, 29, Berlin, Heidelberg, New York, 2019, S. 239 - 249.

Dietmar Jannach, Markus Zanker: Collaborative Filtering: Matrix Completion and Session-BasedRecommendation Tasks. Collaborative Recommendations: Algorithms, Practical Challenges and Applications, World Scientific Publishing, Singapore, 2019, S. 1 - 34.

Dietmar Jannach, Iman Kamehkhosh, Geoffray Bonnin: Music Recommendations. Collaborative Recommendations: Algorithms, Practical Challenges and Applications, World Scientific Publishing, Singapore, 2019, S. 481 - 518.

Sören Köcher, Michael Jugovac, Dietmar Jannach, Hartmut H. Holzmüller: New Hidden Persuaders: An Investigation of Attribute-Level Anchoring Effects of Product Recommendations. Journal of Retailing, Elsevier, 2018, S. 1 - 18.

Mozhgan Karimi, Dietmar Jannach, Michael Jugovac: News Recommender Systems - Survey and Roads Ahead. Information Processing and Management, Elsevier, 54, 2018, S. 1203 - 1227.

Malte Ludewig, Iman Kamehkhosh, Nick Landia, Dietmar Jannach: Effective Nearest-Neighbor Music Recommendations. Proceedings of the ACM RecSys Challenge 2018 Workshop at ACM RecSys 2018, ACM New York, 2018, S. 1 - 6.

Malte Ludewig, Dietmar Jannach: Evaluation of session-based recommendation algorithms. User Modeling and User-Adapted Interaction, Springer Verlag GmbH, 28, Berlin, Heidelberg, New York, 2018, S. 331 - 390.

Michael Jugovac, Dietmar Jannach, Mozhgan Karimi: Streamingrec: a framework for benchmarking stream-based news recommenders. RecSys '18 Proceedings of the 12th ACM Conference on Recommender Systems , ACM New York, 2018, S. 269 - 273.

Dietmar Jannach: Keynote: Session-based Recommendation - Challenges and Recent Advances. Proceedings of the 41st German Conference on Artificial Intelligence, Springer, 11117, Berlin, 2018, S. 3 - 11.

Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach: Sequence-Aware Recommender Systems. ACM Computing Surveys (CSUR), 51, 2018, S. 1 - 36.

Michael Jugovac, Ingrid Nunes, Dietmar Jannach: Investigating the Decision-Making Behavior of Maximizers and Satisficers in the Presence of Recommendations. Proceedings of the 2018 Conference on User Modeling Adaptation and Personalization (UMAP 2018), ACM New York, 2018, S. 279 - 283.

Patrick Walter Koch, Konstantin Schekotihin, Dietmar Jannach, Birgit Hofer, Franz Wotawa, Thomas Schmitz: Combining spreadsheet smells for improved fault prediction. ICSE-NIER '18 Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, ACM New York, 2018, S. 25 - 28.

Heinrich C. Mayr, Judith Michael, Volodymyr Shekhovtsov, Ranapathige Suneth Pubudu Ranasinghe, Claudia Steinberger: A Model Centered Perspective on Software-Intensive Systems. Proceedings of the 9th International Workshop on Enterprise Modeling and Information Systems Architectures (EMISA 2018) , 2018, S. 58 - 64.

Dietmar Jannach, Lukas Lerche, Markus Zanker: Recommending Based on Implicit Feedback. Social Information Access, Springer, Berlin, 2018, S. 510 - 569.

Konstantin Schekotihin, Dietmar Jannach, Thomas Schmitz: Parallel Model-Based Diagnosis. Handbook of Parallel Constraint Reasoning, Springer, Berlin, 2018, S. 547 - 580.

Iman Kamehkhosh, Dietmar Jannach, Geoffray Bonnin: How Automated Recommendations Affect the Playlist Creation Behavior of Users. Proceedings of the Workshop on Intelligent Music Interfaces for Listening and Creation at IUI 2018, 2068, 2018, S. 1 - 6.

Claudia Steinberger, Judith Michael: Towards Cognitive Assisted Living 3.0. 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), IEEE, Piscataway (NJ), 2018, S. 687 - 692.

Malte Ludewig, Dietmar Jannach: Could You Play That Song Again? – Reminding Users of Their Favorite Tracks Through Recommendations. Proceedings of the WSDM 2018 Cup Workshop, WSDM’18 Cup, Los Angeles, 2018, S. 1 - 5.

Josef Bauer, Dietmar Jannach: Optimal Pricing in E-Commerce Based on Sparse and Noisy Data. Decision Support Systems, Elsevier, 106, 2018, S. 53 - 63.

Judith Michael, Claudia Steinberger, Vladimir A. Shekhovtsov, Fadi Al Machot, Ranapathige Suneth Pubudu Ranasinghe, Gert Morak: The HBMS Story. Enterprise Modelling and Information Systems Architectures, 13, 2018, S. 345 - 370.

Patrick Koch, Konstantin Schekotihin, Dietmar Jannach, Birgit Hofer, Franz Wotawa: Combining spreadsheet smells for improved fault prediction. . Proceedings of the 40th International Conference on Software Engineering, ACM Digital Library, New York, NY, 2018, S. 25 - 28.

Judith Michael, Claudia Steinberger: Context Modeling for Active Assistance. Proceedings of the ER Forum 2017 and the ER 2017 Demo Track co-located with the 36th International Conference on Conceptual Modelling (ER 2017), CEUR Workshop Proceedings (CEUR-WS.org), Aachen, 2017, S. 221 - 234.