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DEPARTMENT OF ARTIFICIAL INTELLIGENCE AND CYBERSECURITY

AAU1/...Department of Artificial Intelligence and Cybersecurity2/Research Groups3/Research Group Information Systems4/Publications

Publications

INFSYS Publications (coming from CRIS)

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

  • 2019
  • 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.

  • 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: 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.

  • 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.

  • 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,

  • 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.

  • 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.

  • 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, 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.

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

  • 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.

  • 2018
  • 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.

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

  • 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.

  • 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.

  • 2017
  • 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.

Some INFSYS publications have not been available yet in the University Research Information System (CRIS) or have been published before authors became members of the Alpen-Adria-Universität Klagenfurt. These publications can be found on the personal homepages in the ‘Team’ menu on the right.

-> Note that the publication lists in the University Research Information System (CRIS) might be incomplete. More information can be found on the personal homepages of the team members.

All Publications of the Department of Artificial Intelligence and Cybersecurity (AICS) can also be found in the University Research Information System (CRIS).

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