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ORCIDDietmar Jannach
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- affiliation: University of Klagenfurt, Austria
- affiliation: University of Bergen, Norway
- affiliation (former): Dortmund University of Technology, Germany
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2020 – today
- 2024
[j97]Nicholas Diakopoulos
, Christoph Trattner, Dietmar Jannach, Irene Costera Meijer, Enrico Motta:
Leveraging Professional Ethics for Responsible AI. Commun. ACM 67(2): 19-21 (2024)- [j96]Alvise De Biasio, Nicolò Navarin, Dietmar Jannach:
Economic recommender systems - a systematic review. Electron. Commer. Res. Appl. 63: 101352 (2024) - [j95]Alvise De Biasio, Dietmar Jannach, Nicolò Navarin:
Model-based approaches to profit-aware recommendation. Expert Syst. Appl. 249: 123642 (2024) - [j94]Dietmar Jannach, Himan Abdollahpouri:
A survey on multi-objective recommender systems. Frontiers Big Data 6 (2024) - [j93]Lina Yao, Julian J. McAuley, Xianzhi Wang, Dietmar Jannach:
Special Issue on Responsible Recommender Systems Part 1. ACM Trans. Intell. Syst. Technol. 15(4): 72:1-72:3 (2024) - [j92]Yashar Deldjoo, Dietmar Jannach, Alejandro Bellogín, Alessandro Difonzo, Dario Zanzonelli:
Fairness in recommender systems: research landscape and future directions. User Model. User Adapt. Interact. 34(1): 59-108 (2024) - [j91]Gabrielle Alves, Dietmar Jannach, Rodrigo Ferrari de Souza, Daniela E. Damian, Marcelo Garcia Manzato:
Digitally nudging users to explore off-profile recommendations: here be dragons. User Model. User Adapt. Interact. 34(2): 441-481 (2024) - [j90]Josef Bauer, Dietmar Jannach:
Hybrid session-aware recommendation with feature-based models. User Model. User Adapt. Interact. 34(3): 691-728 (2024) - [c162]Patrick Rodler, Erich Teppan, Dietmar Jannach:
Summary of "Randomized Problem-Relaxation Solving for Over-Constrained Schedules" (Extended Abstract). DX 2024: 33:1-33:4 - [c161]Faisal Shehzad, Dietmar Jannach:
Performance Comparison of Session-Based Recommendation Algorithms Based on GNNs. ECIR (4) 2024: 115-131 - [c160]Matteo Attimonelli, Claudio Pomo, Dietmar Jannach, Tommaso Di Noia:
Toward Effective Fashion Item Compatibility Modelling. IIR 2024: 111-114 - [c159]Adil Mukhtar, Dietmar Jannach, Franz Wotawa:
Investigating Reproducibility in Deep Learning-Based Software Fault Prediction. QRS 2024: 306-317 - [c158]Gabrielle Alves, Dietmar Jannach, Rodrigo Ferrari de Souza, Marcelo Garcia Manzato:
User Perception of Fairness-Calibrated Recommendations. UMAP 2024: 78-88 - [c157]Ahtsham Manzoor, Samuel C. Ziegler, Klaus Maria Pirker Garcia, Dietmar Jannach:
ChatGPT as a Conversational Recommender System: A User-Centric Analysis. UMAP 2024: 267-272 - [c156]Laurens Rook, Markus Zanker, Dietmar Jannach:
Are We Losing Interest in Context-Aware Recommender Systems? UMAP (Adjunct Publication) 2024 - [d3]Adil Mukhtar, Dietmar Jannach, Franz Wotawa:
Investigating Reproducibility in Deep Learning-Based Software Fault Prediction. Version 1. Zenodo, 2024 [all versions]
- [d2]Adil Mukhtar, Dietmar Jannach, Franz Wotawa:
Investigating Reproducibility in Deep Learning-Based Software Fault Prediction. Version 2. Zenodo, 2024 [all versions] - [i50]Artun Boz, Wouter Zorgdrager, Zoe Kotti, Jesse Harte, Panos Louridas, Dietmar Jannach, Marios Fragkoulis:
Improving Sequential Recommendations with LLMs. CoRR abs/2402.01339 (2024) - [i49]Adil Mukhtar, Dietmar Jannach, Franz Wotawa:
Investigating Reproducibility in Deep Learning-Based Software Fault Prediction. CoRR abs/2402.05645 (2024) - [i48]Jin Li, Shoujin Wang, Qi Zhang, Longbing Cao, Fang Chen, Xiuzhen Zhang, Dietmar Jannach, Charu C. Aggarwal:
Causal Learning for Trustworthy Recommender Systems: A Survey. CoRR abs/2402.08241 (2024) - [i47]Dietmar Jannach, Markus Zanker:
A Survey on Intent-aware Recommender Systems. CoRR abs/2406.16350 (2024) - [i46]Matteo Attimonelli, Claudio Pomo, Dietmar Jannach, Tommaso Di Noia:
Fashion Image-to-Image Translation for Complementary Item Retrieval. CoRR abs/2408.09847 (2024) - 2023
- [j89]Dietmar Jannach:
Evaluating conversational recommender systems. Artif. Intell. Rev. 56(3): 2365-2400 (2023) - [j88]Adil Mukhtar, Birgit Hofer, Dietmar Jannach, Franz Wotawa:
Explaining software fault predictions to spreadsheet users. J. Syst. Softw. 201: 111676 (2023) - [j87]Christine Bauer, Ben Carterette, Nicola Ferro, Norbert Fuhr, Joeran Beel, Timo Breuer, Charles L. A. Clarke, Anita Crescenzi, Gianluca Demartini, Giorgio Maria Di Nunzio, Laura Dietz, Guglielmo Faggioli, Bruce Ferwerda, Maik Fröbe, Matthias Hagen, Allan Hanbury, Claudia Hauff, Dietmar Jannach, Noriko Kando, Evangelos Kanoulas, Bart P. Knijnenburg, Udo Kruschwitz, Meijie Li, Maria Maistro, Lien Michiels, Andrea Papenmeier, Martin Potthast, Paolo Rosso, Alan Said, Philipp Schaer, Christin Seifert, Damiano Spina, Benno Stein, Nava Tintarev, Julián Urbano, Henning Wachsmuth, Martijn C. Willemsen, Justin Zobel:
Report on the Dagstuhl Seminar on Frontiers of Information Access Experimentation for Research and Education. SIGIR Forum 57(1): 7:1-7:28 (2023) - [j86]Li Chen, Dietmar Jannach:
ACM Transactions on Recommender Systems: Inaugural Issue Editorial. Trans. Recomm. Syst. 1(1): 1 (2023) - [j85]Veronika Bogina, Tsvi Kuflik, Dietmar Jannach, Mária Bieliková, Michal Kompan, Christoph Trattner:
Considering temporal aspects in recommender systems: a survey. User Model. User Adapt. Interact. 33(1): 81-119 (2023) - [j84]Mathias Jesse, Christine Bauer, Dietmar Jannach:
Intra-list similarity and human diversity perceptions of recommendations: the details matter. User Model. User Adapt. Interact. 33(4): 769-802 (2023) - [c155]Ahtsham Manzoor, Wanling Cai, Dietmar Jannach:
Factors Influencing the Perceived Meaningfulness of System Responses in Conversational Recommendation. IntRS@RecSys 2023: 19-34 - [c154]Dietmar Jannach:
Sequential and Session-based Recommendation: Past, Present, Future. ORSUM@RecSys 2023 - [c153]Faisal Shehzad, Dietmar Jannach:
Everyone's a Winner! On Hyperparameter Tuning of Recommendation Models. RecSys 2023: 652-657 - [c152]Anastasiia Klimashevskaia, Mehdi Elahi, Dietmar Jannach, Lars Skjærven, Astrid Tessem, Christoph Trattner:
Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study. RecSys 2023: 1084-1089 - [c151]Jesse Harte, Wouter Zorgdrager, Panos Louridas, Asterios Katsifodimos, Dietmar Jannach, Marios Fragkoulis:
Leveraging Large Language Models for Sequential Recommendation. RecSys 2023: 1096-1102 - [c150]Siyu Wang, Xiaocong Chen, Dietmar Jannach, Lina Yao:
Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning. SIGIR 2023: 1599-1608 - [c149]Koby Bibas, Oren Sar Shalom, Dietmar Jannach:
Semi-supervised Adversarial Learning for Complementary Item Recommendation. WWW 2023: 1804-1812 - [i45]Pablo Castells, Dietmar Jannach:
Recommender Systems: A Primer. CoRR abs/2302.02579 (2023) - [i44]Koby Bibas, Oren Sar Shalom, Dietmar Jannach:
Semi-supervised Adversarial Learning for Complementary Item Recommendation. CoRR abs/2303.05812 (2023) - [i43]Siyu Wang, Xiaocong Chen, Dietmar Jannach, Lina Yao:
Causal Decision Transformer for Recommender Systems via Offline Reinforcement Learning. CoRR abs/2304.07920 (2023) - [i42]Anastasiia Klimashevskaia, Dietmar Jannach, Mehdi Elahi, Christoph Trattner:
A Survey on Popularity Bias in Recommender Systems. CoRR abs/2308.01118 (2023) - [i41]Zehui Wang, Wolfram Höpken, Dietmar Jannach:
A Survey on Point-of-Interest Recommendations Leveraging Heterogeneous Data. CoRR abs/2308.07426 (2023) - [i40]Xiaocong Chen, Siyu Wang, Julian J. McAuley, Dietmar Jannach, Lina Yao:
On the Opportunities and Challenges of Offline Reinforcement Learning for Recommender Systems. CoRR abs/2308.11336 (2023) - [i39]Alvise De Biasio, Nicolò Navarin, Dietmar Jannach:
Economic Recommender Systems - A Systematic Review. CoRR abs/2308.11998 (2023) - [i38]Jesse Harte, Wouter Zorgdrager, Panos Louridas, Asterios Katsifodimos, Dietmar Jannach, Marios Fragkoulis:
Leveraging Large Language Models for Sequential Recommendation. CoRR abs/2309.09261 (2023) - [i37]Eduardo Witter dos Santos, Ingrid Nunes, Dietmar Jannach:
Team-related Features in Code Review Prediction Models. CoRR abs/2312.06244 (2023) - [i36]Faisal Shehzad, Dietmar Jannach:
Performance Comparison of Session-based Recommendation Algorithms based on GNNs. CoRR abs/2312.16695 (2023) - 2022
- [j83]Mehdi Elahi, Dietmar Jannach, Lars Skjærven, 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 Ethics 2(1): 103-114 (2022) - [j82]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 Ethics 2(4): 585-594 (2022) - [j81]Dietmar Jannach, Pearl Pu, Francesco Ricci, Markus Zanker:
Recommender Systems: Trends and Frontiers. AI Mag. 43(2): 145-150 (2022) - [j80]Dietmar Jannach, Li Chen:
Conversational Recommendation: A Grand AI Challenge. AI Mag. 43(2): 151-163 (2022) - [j79]Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, Li Chen:
A Survey on Conversational Recommender Systems. ACM Comput. Surv. 54(5): 105:1-105:36 (2022) - [j78]Nada Ghanem, Stephan Leitner, Dietmar Jannach:
Balancing consumer and business value of recommender systems: A simulation-based analysis. Electron. Commer. Res. Appl. 55: 101195 (2022) - [j77]Ahtsham Manzoor, Dietmar Jannach:
Towards retrieval-based conversational recommendation. Inf. Syst. 109: 102083 (2022) - [j76]Sara Latifi, Dietmar Jannach, Andrés Ferraro:
Sequential recommendation: A study on transformers, nearest neighbors and sampled metrics. Inf. Sci. 609: 660-678 (2022) - [j75]Tommaso Di Noia, Francesco Maria Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo:
Conversational recommendation: Theoretical model and complexity analysis. Inf. Sci. 614: 325-347 (2022) - [j74]Adil Mukhtar, Birgit Hofer, Dietmar Jannach, Franz Wotawa:
Spreadsheet debugging: The perils of tool over-reliance. J. Syst. Softw. 184: 111119 (2022) - [c148]Anastasiia Klimashevskaia, Mehdi Elahi, Dietmar Jannach, Christoph Trattner, Lars Skjærven:
Mitigating Popularity Bias in Recommendation: Potential and Limits of Calibration Approaches. BIAS 2022: 82-90 - [c147]Koby Bibas, Oren Sar Shalom, Dietmar Jannach:
Collaborative Image Understanding. CIKM 2022: 77-87 - [c146]Tommaso Di Noia, Francesco Maria Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo:
Towards a theoretical formalization of conversational recommendation. CIKM Workshops 2022 - [c145]Ahtsham Manzoor, Dietmar Jannach:
Revisiting Retrieval-based Approaches for Conversational Recommender Systems. IIR 2022 - [c144]Adil Mukhtar, Birgit Hofer, Dietmar Jannach, Franz Wotawa, Konstantin Schekotihin:
Boosting Spectrum-Based Fault Localization for Spreadsheets with Product Metrics in a Learning Approach. ASE 2022: 175:1-175:5 - [c143]Dietmar Jannach:
Multi-Objective Recommendation: Overview and Challenges. MORS@RecSys 2022 - [c142]Ahtsham Manzoor, Dietmar Jannach:
INFACT: An Online Human Evaluation Framework for Conversational Recommendation. KaRS@RecSys 2022: 6-11 - [c141]Ahtsham Manzoor, Dietmar Jannach:
INSPIRED2: An Improved Dataset for Sociable Conversational Recommendation. KaRS@RecSys 2022: 73-80 - [c140]Sara Latifi, Dietmar Jannach:
Streaming Session-Based Recommendation: When Graph Neural Networks meet the Neighborhood. RecSys 2022: 420-426 - [c139]Sagi Eden, Amit Livne, Oren Sar Shalom, Bracha Shapira, Dietmar Jannach:
Investigating the Value of Subtitles for Improved Movie Recommendations. UMAP 2022: 99-109 - [c138]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo:
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art. UMAP 2022: 121-131 - [r6]Dietmar Jannach, Massimo Quadrana, Paolo Cremonesi:
Session-Based Recommender Systems. Recommender Systems Handbook 2022: 301-334 - [r5]Dietmar Jannach, Markus Zanker:
Value and Impact of Recommender Systems. Recommender Systems Handbook 2022: 519-546 - [d1]Nada Ghanem, Stephan Leitner, Dietmar Jannach:
Dataset: "Balancing consumer and business value of recommender systems: A simulation-based analysis". Zenodo, 2022 - [i35]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo:
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art. CoRR abs/2203.01155 (2022) - [i34]Nada Ghanem, Stephan Leitner, Dietmar Jannach:
Balancing Consumer and Business Value of Recommender Systems: A Simulation-based Analysis. CoRR abs/2203.05952 (2022) - [i33]Dietmar Jannach, Li Chen:
Conversational Recommendation: A Grand AI Challenge. CoRR abs/2203.09126 (2022) - [i32]Yashar Deldjoo, Dietmar Jannach, Alejandro Bellogín, Alessandro Difonzo, Dario Zanzonelli:
A Survey of Research on Fair Recommender Systems. CoRR abs/2205.11127 (2022) - [i31]Ahtsham Manzoor, Dietmar Jannach:
INSPIRED2: An Improved Dataset for Sociable Conversational Recommendation. CoRR abs/2208.04104 (2022) - [i30]Dietmar Jannach:
Evaluating Conversational Recommender Systems. CoRR abs/2208.12061 (2022) - [i29]Ahtsham Manzoor, Dietmar Jannach:
INFACT: An Online Human Evaluation Framework for Conversational Recommendation. CoRR abs/2209.03213 (2022) - [i28]Dietmar Jannach:
Multi-Objective Recommender Systems: Survey and Challenges. CoRR abs/2210.10309 (2022) - [i27]Koby Bibas, Oren Sar Shalom, Dietmar Jannach:
Collaborative Image Understanding. CoRR abs/2210.11907 (2022) - 2021
- [j73]Dietmar Jannach, Pearl Pu, Francesco Ricci, Markus Zanker:
Recommender Systems: Past, Present, Future. AI Mag. 42(3): 3-6 (2021) - [j72]Paolo Cremonesi, Dietmar Jannach:
Progress in Recommender Systems Research: Crisis? What Crisis? AI Mag. 42(3): 43-54 (2021) - [j71]Sara Latifi, Noemi Mauro, Dietmar Jannach:
Session-aware recommendation: A surprising quest for the state-of-the-art. Inf. Sci. 573: 291-315 (2021) - [j70]Birgit Hofer, Dietmar Jannach, Patrick W. Koch, Konstantin Schekotihin, Franz Wotawa:
Product metrics for spreadsheets - A systematic review. J. Syst. Softw. 175: 110910 (2021) - [j69]Josef Bauer, Dietmar Jannach:
Improved Customer Lifetime Value Prediction With Sequence-To-Sequence Learning and Feature-Based Models. ACM Trans. Knowl. Discov. Data 15(5): 80:1-80:37 (2021) - [j68]Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach:
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research. ACM Trans. Inf. Syst. 39(2): 20:1-20:49 (2021) - [j67]Patrick W. Koch, Konstantin Schekotihin, Dietmar Jannach, Birgit Hofer, Franz Wotawa:
Metric-Based Fault Prediction for Spreadsheets. IEEE Trans. Software Eng. 47(10): 2195-2207 (2021) - [j66]Malte Ludewig, Noemi Mauro, Sara Latifi, Dietmar Jannach:
Empirical analysis of session-based recommendation algorithms. User Model. User Adapt. Interact. 31(1): 149-181 (2021) - [c137]Karin Hodnigg, Christian Macho, Martin Pinzger, Dietmar Jannach:
Comprehending Spreadsheets: Which Strategies do Users Apply? ICPC 2021: 386-390 - [c136]Patrick Rodler, Erich Teppan, Dietmar Jannach:
Randomized Problem-Relaxation Solving for Over-Constrained Schedules. KR 2021: 696-701 - [c135]Mathias Jesse, Dietmar Jannach:
Explorations in Digital Nudging for Online Food Choices. PACIS 2021: 209 - [c134]Fatih Gedikli, Anne Stockem Novo, Dietmar Jannach:
Semi-Automated Identification of News Story Chains: A New Dataset and Entity-based Labeling Method. INRA@RecSys 2021: 29-42 - [c133]Ahtsham Manzoor, Dietmar Jannach:
Generation-based vs. Retrieval-based Conversational Recommendation: A User-Centric Comparison. RecSys 2021: 515-520 - [c132]Dietmar Jannach, Mathias Jesse, Michael Jugovac, Christoph Trattner:
Exploring Multi-List User Interfaces for Similar-Item Recommendations. UMAP 2021: 224-228 - [c131]Rami Cohen, Oren Sar Shalom, Dietmar Jannach, Amihood Amir:
A Black-Box Attack Model for Visually-Aware Recommender Systems. WSDM 2021: 94-102 - [i26]Gediminas Adomavicius, Dietmar Jannach, Stephan Leitner, Jingjing Zhang:
Understanding Longitudinal Dynamics of Recommender Systems with Agent-Based Modeling and Simulation. CoRR abs/2108.11068 (2021) - [i25]Ahtsham Manzoor, Dietmar Jannach:
Towards Retrieval-based Conversational Recommendation. CoRR abs/2109.02311 (2021) - [i24]Tommaso Di Noia, Francesco M. Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo:
Conversational Recommendation: Theoretical Model and Complexity Analysis. CoRR abs/2111.05578 (2021) - 2020
- [j65]Dietmar Jannach, Christine Bauer:
Escaping the McNamara Fallacy: Towards more Impactful Recommender Systems Research. AI Mag. 41(4): 79-95 (2020) - [j64]Christoph Trattner, Dietmar Jannach:
Learning to recommend similar items from human judgments. User Model. User Adapt. Interact. 30(1): 1-49 (2020) - [j63]Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato:
Multistakeholder recommendation: Survey and research directions. User Model. User Adapt. Interact. 30(1): 127-158 (2020) - [j62]Iman Kamehkhosh, Geoffray Bonnin, Dietmar Jannach:
Effects of recommendations on the playlist creation behavior of users. User Model. User Adapt. Interact. 30(2): 285-322 (2020) - [j61]Dietmar Jannach, Bamshad Mobasher, Shlomo Berkovsky:
Research directions in session-based and sequential recommendation. User Model. User Adapt. Interact. 30(4): 609-616 (2020) - [c130]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 2020: 355-363 - [c129]Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach:
Methodological Issues in Recommender Systems Research (Extended Abstract). IJCAI 2020: 4706-4710 - [c128]Dietmar Jannach, Gabriel de Souza Pereira Moreira, Even Oldridge:
Why Are Deep Learning Models Not Consistently Winning Recommender Systems Competitions Yet?: A Position Paper. RecSys Challenge 2020: 44-49 - [c127]Dietmar Jannach, Ahtsham Manzoor:
End-to-End Learning for Conversational Recommendation: A Long Way to Go? IntRS@RecSys 2020: 72-76 - [c126]Andres Ferraro, Dietmar Jannach, Xavier Serra:
Exploring Longitudinal Effects of Session-based Recommendations. RecSys 2020: 474-479 - [c125]Oren Sar Shalom, Dietmar Jannach, Joseph A. Konstan:
Second Workshop on the Impact of Recommender Systems at ACM RecSys '20. RecSys 2020: 630-631 - [c124]Dietmar Jannach, Surya Kallumadi, Tracy Holloway King, Weihua Luo, Shervin Malmasi:
ECOM'20: The SIGIR 2020 Workshop on eCommerce. SIGIR 2020: 2459-2460 - [e14]Toine Bogers, Marijn Koolen, Casper Petersen, Bamshad Mobasher, Alexander Tuzhilin, Oren Sar Shalom, Dietmar Jannach, Joseph A. Konstan:
Proceedings of the Workshops on Recommendation in Complex Scenarios and the Impact of Recommender Systems co-located with 14th ACM Conference on Recommender Systems (RecSys 2020), Online, September 25, 2020. CEUR Workshop Proceedings 2697, CEUR-WS.org 2020 [contents] - [i23]Dietmar Jannach, Ahtsham Manzoor, Wanling Cai, Li Chen:
A Survey on Conversational Recommender Systems. CoRR abs/2004.00646 (2020) - [i22]Ingrid Nunes, Dietmar Jannach:
A systematic review and taxonomy of explanations in decision support and recommender systems. CoRR abs/2006.08672 (2020) - [i21]Gabriel de Souza Pereira Moreira, Dietmar Jannach, Adilson Marques da Cunha:
Hybrid Session-based News Recommendation using Recurrent Neural Networks. CoRR abs/2006.13063 (2020) - [i20]Maurizio Ferrari Dacrema, Federico Parroni, Paolo Cremonesi, Dietmar Jannach:
Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems. CoRR abs/2007.11893 (2020) - [i19]Stephan Leitner, Bartosz Gula, Dietmar Jannach, Ulrike Krieg-Holz, Friederike Wall:
Infodemics: A call to action for interdisciplinary research. CoRR abs/2007.12226 (2020) - [i18]Andres Ferraro, Dietmar Jannach, Xavier Serra:
Exploring Longitudinal Effects of Session-based Recommendations. CoRR abs/2008.07226 (2020) - [i17]Rami Cohen, Oren Sar Shalom, Dietmar Jannach, Amihood Amir:
A Black-Box Attack Model for Visually-Aware Recommender Systems. CoRR abs/2011.02701 (2020) - [i16]Mathias Jesse, Dietmar Jannach:
Digital Nudging with Recommender Systems: Survey and Future Directions. CoRR abs/2011.03413 (2020) - [i15]Sara Latifi, Noemi Mauro, Dietmar Jannach:
Session-aware Recommendation: A Surprising Quest for the State-of-the-art. CoRR abs/2011.03424 (2020)
2010 – 2019
- 2019
- [j60]Gabriel de Souza Pereira Moreira, Dietmar Jannach, Adilson Marques da Cunha:
Contextual Hybrid Session-Based News Recommendation With Recurrent Neural Networks. IEEE Access 7: 169185-169203 (2019) - [j59]Dietmar Jannach, Thomas Schmitz, Birgit Hofer, Konstantin Schekotihin, Patrick W. Koch, Franz Wotawa:
Fragment-based spreadsheet debugging. Autom. Softw. Eng. 26(1): 203-239 (2019) - [j58]Markus Zanker, Laurens Rook, Dietmar Jannach:
Measuring the impact of online personalisation: Past, present and future. Int. J. Hum. Comput. Stud. 131: 160-168 (2019) - [j57]Patrick Rodler, Dietmar Jannach, Konstantin Schekotihin, Philipp Fleiss:
Are query-based ontology debuggers really helping knowledge engineers? Knowl. Based Syst. 179: 92-107 (2019) - [j56]Dietmar Jannach, Michael Jugovac:
Measuring the Business Value of Recommender Systems. ACM Trans. Manag. Inf. Syst. 10(4): 16:1-16:23 (2019) - [j55]Pasquale Lops, Dietmar Jannach, Cataldo Musto, Toine Bogers, Marijn Koolen:
Trends in content-based recommendation - Preface to the special issue on Recommender systems based on rich item descriptions. User Model. User Adapt. Interact. 29(2): 239-249 (2019) - [c123]Dietmar Jannach, Michael Jugovac, Ingrid Nunes:
Explanations and User Control in Recommender Systems. ABIS@HT 2019: 31 - [c122]Dietmar Jannach, Oren Sar Shalom, Joseph A. Konstan:
Towards More Impactful Recommender Systems Research. ImpactRS@RecSys 2019 - [c121]Malte Ludewig, Dietmar Jannach:
Learning to rank hotels for search and recommendation from session-based interaction logs and meta data. RecSys Challenge 2019: 5:1-5:5 - [c120]Gabriel de Souza Pereira Moreira, Dietmar Jannach, Adilson Marques da Cunha:
On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems. INRA@RecSys 2019: 18-23 - [c119]Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach:
Are we really making much progress? A worrying analysis of recent neural recommendation approaches. RecSys 2019: 101-109 - [c118]Malte Ludewig, Noemi Mauro, Sara Latifi, Dietmar Jannach:
Performance comparison of neural and non-neural approaches to session-based recommendation. RecSys 2019: 462-466 - [c117]Malte Ludewig, Dietmar Jannach:
User-centric evaluation of session-based recommendations for an automated radio station. RecSys 2019: 516-520 - [c116]Oren Sar Shalom, Dietmar Jannach, Ido Guy:
First workshop on the impact of recommender systems at ACM RecSys 2019. RecSys 2019: 556-557 - [c115]Dietmar Jannach, Olga C. Santos:
Session details: ACM UMAP 2019 Main Track. UMAP 2019 - [c114]Massimo Quadrana, Dietmar Jannach, Paolo Cremonesi:
Tutorial: Sequence-Aware Recommender Systems. WWW (Companion Volume) 2019: 1316 - [e13]Oren Sar Shalom, Dietmar Jannach, Ido Guy:
Proceedings of the 1st Workshop on the Impact of Recommender Systems co-located with 13th ACM Conference on Recommender Systems, ImpactRS@RecSys 2019), Copenhagen, Denmark, September 19, 2019. CEUR Workshop Proceedings 2462, CEUR-WS.org 2019 [contents] - [e12]George Angelos Papadopoulos, George Samaras, Stephan Weibelzahl, Dietmar Jannach, Olga C. Santos:
Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2019, Larnaca, Cyprus, June 9-12, 2019. ACM 2019, ISBN 978-1-4503-6021-0 [contents] - [e11]George Angelos Papadopoulos, George Samaras, Stephan Weibelzahl, Dietmar Jannach, Olga C. Santos:
Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization, UMAP 2019, Larnaca, Cyprus, June 09-12, 2019. ACM 2019, ISBN 978-1-4503-6711-0 [contents] - [i14]Patrick Rodler, Dietmar Jannach, Konstantin Schekotihin, Philipp Fleiss:
Are Query-Based Ontology Debuggers Really Helping Knowledge Engineers? CoRR abs/1904.01484 (2019) - [i13]Gabriel de Souza Pereira Moreira, Dietmar Jannach, Adilson Marques da Cunha:
Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks. CoRR abs/1904.10367 (2019) - [i12]Himan Abdollahpouri, Gediminas Adomavicius, Robin Burke, Ido Guy, Dietmar Jannach, Toshihiro Kamishima, Jan Krasnodebski, Luiz Augusto Pizzato:
Beyond Personalization: Research Directions in Multistakeholder Recommendation. CoRR abs/1905.01986 (2019) - [i11]Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach:
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches. CoRR abs/1907.06902 (2019) - [i10]Gabriel de Souza Pereira Moreira, Dietmar Jannach, Adilson Marques da Cunha:
On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems. CoRR abs/1907.07629 (2019) - [i9]Dietmar Jannach, Michael Jugovac:
Measuring the Business Value of Recommender Systems. CoRR abs/1908.08328 (2019) - [i8]Malte Ludewig, Noemi Mauro, Sara Latifi, Dietmar Jannach:
Empirical Analysis of Session-Based Recommendation Algorithms. CoRR abs/1910.12781 (2019) - [i7]Maurizio Ferrari Dacrema, Simone Boglio, Paolo Cremonesi, Dietmar Jannach:
A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research. CoRR abs/1911.07698 (2019) - 2018
- [j54]Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach:
Sequence-Aware Recommender Systems. ACM Comput. Surv. 51(4): 66:1-66:36 (2018) - [j53]Josef Bauer, Dietmar Jannach:
Optimal pricing in e-commerce based on sparse and noisy data. Decis. Support Syst. 106: 53-63 (2018) - [j52]Mozhgan Karimi, Dietmar Jannach, Michael Jugovac:
News recommender systems - Survey and roads ahead. Inf. Process. Manag. 54(6): 1203-1227 (2018) - [j51]Malte Ludewig, Dietmar Jannach:
Evaluation of session-based recommendation algorithms. User Model. User Adapt. Interact. 28(4-5): 331-390 (2018) - [c113]Patrick W. Koch, Konstantin Schekotihin, Dietmar Jannach, Birgit Hofer, Franz Wotawa, Thomas Schmitz:
Combining spreadsheet smells for improved fault prediction. ICSE (NIER) 2018: 25-28 - [c112]Iman Kamehkhosh, Dietmar Jannach, Geoffray Bonnin:
How Automated Recommendations Affect the Playlist Creation Behavior of Users. IUI Workshops 2018 - [c111]Dietmar Jannach:
Keynote: Session-Based Recommendation - Challenges and Recent Advances. KI 2018: 3-7 - [c110]Malte Ludewig, Iman Kamehkhosh, Nick Landia, Dietmar Jannach:
Effective Nearest-Neighbor Music Recommendations. RecSys Challenge 2018: 3:1-3:6 - [c109]Michael Jugovac, Dietmar Jannach, Mozhgan Karimi:
Streamingrec: a framework for benchmarking stream-based news recommenders. RecSys 2018: 269-273 - [c108]Michael Jugovac, Ingrid Nunes, Dietmar Jannach:
Investigating the Decision-Making Behavior of Maximizers and Satisficers in the Presence of Recommendations. UMAP 2018: 279-283 - [c107]Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach:
Sequence-aware Recommender Systems. UMAP 2018: 373-374 - [p8]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Thomas Schmitz:
Parallel Model-Based Diagnosis. Handbook of Parallel Constraint Reasoning 2018: 547-580 - [p7]Dietmar Jannach, Markus Zanker:
Collaborative Filtering: Matrix Completion and Session-Based Recommendation Tasks. Collaborative Recommendations 2018: 1-34 - [p6]Dietmar Jannach, Iman Kamehkhosh, Geoffray Bonnin:
Music Recommendations. Collaborative Recommendations 2018: 481-518 - [p5]Dietmar Jannach, Lukas Lerche, Markus Zanker:
Recommending Based on Implicit Feedback. Social Information Access 2018: 510-569 - [r4]Fatih Gedikli, Dietmar Jannach:
Recommender Systems, Semantic-Based. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i6]Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach:
Sequence-Aware Recommender Systems. CoRR abs/1802.08452 (2018) - [i5]Malte Ludewig, Dietmar Jannach:
Evaluation of Session-based Recommendation Algorithms. CoRR abs/1803.09587 (2018) - [i4]Patrick W. Koch, Konstantin Schekotihin, Dietmar Jannach, Birgit Hofer, Franz Wotawa:
Combining Spreadsheet Smells for Improved Fault Prediction. CoRR abs/1805.10493 (2018) - 2017
- [j50]Michael Jugovac, Dietmar Jannach, Lukas Lerche:
Efficient optimization of multiple recommendation quality factors according to individual user tendencies. Expert Syst. Appl. 81: 321-331 (2017) - [j49]Tommaso Di Noia, Dietmar Jannach:
Preface to the Special Issue on Recommender Systems. J. Data Semant. 6(1): 1 (2017) - [j48]Michael Jugovac, Dietmar Jannach:
Interacting with Recommenders - Overview and Research Directions. ACM Trans. Interact. Intell. Syst. 7(3): 10:1-10:46 (2017) - [j47]Dietmar Jannach, Malte Ludewig, Lukas Lerche:
Session-based item recommendation in e-commerce: on short-term intents, reminders, trends and discounts. User Model. User Adapt. Interact. 27(3-5): 351-392 (2017) - [j46]Ingrid Nunes, Dietmar Jannach:
A systematic review and taxonomy of explanations in decision support and recommender systems. User Model. User Adapt. Interact. 27(3-5): 393-444 (2017) - [c106]Dietmar Jannach, Malte Ludewig:
Investigating Personalized Search in E-Commerce. FLAIRS 2017: 645-650 - [c105]Dietmar Jannach, Ingrid Nunes, Michael Jugovac:
Interacting with Recommender Systems. IUI Companion 2017: 25-27 - [c104]Dietmar Jannach:
Interacting with Recommenders. IntRS@RecSys 2017: 1 - [c103]Dietmar Jannach:
Challenges of Session-Aware Recommendation in E-Commerce. ComplexRec@RecSys 2017: 3-4 - [c102]Iman Kamehkhosh, Dietmar Jannach, Malte Ludewig:
A Comparison of Frequent Pattern Techniques and a Deep Learning Method for Session-Based Recommendation. RecTemp@RecSys 2017: 50-56 - [c101]Dietmar Jannach, Malte Ludewig:
When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation. RecSys 2017: 306-310 - [c100]Dietmar Jannach, Iman Kamehkhosh, Lukas Lerche:
Leveraging multi-dimensional user models for personalized next-track music recommendation. SAC 2017: 1635-1642 - [c99]Dietmar Jannach, Malte Ludewig:
Determining characteristics of successful recommendations from log data: a case study. SAC 2017: 1643-1648 - [c98]Dietmar Jannach, Lukas Lerche:
Offline performance vs. subjective quality experience: a case study in video game recommendation. SAC 2017: 1649-1654 - [c97]Iman Kamehkhosh, Dietmar Jannach:
User Perception of Next-Track Music Recommendations. UMAP 2017: 113-121 - [c96]Thomas Schmitz, Dietmar Jannach, Birgit Hofer, Patrick W. Koch, Konstantin Schekotihin, Franz Wotawa:
A decomposition-based approach to spreadsheet testing and debugging. VL/HCC 2017: 117-121 - [c95]Thomas Schmitz, Dietmar Jannach:
An Al-based interactive tool for spreadsheet debugging. VL/HCC 2017: 333-334 - [i3]Dietmar Jannach, Gediminas Adomavicius:
Price and Profit Awareness in Recommender Systems. CoRR abs/1707.08029 (2017) - 2016
- [j45]Dietmar Jannach, Thomas Schmitz:
Model-based diagnosis of spreadsheet programs: a constraint-based debugging approach. Autom. Softw. Eng. 23(1): 105-144 (2016) - [j44]Dietmar Jannach, Paul Resnick, Alexander Tuzhilin, Markus Zanker:
Recommender systems - : beyond matrix completion. Commun. ACM 59(11): 94-102 (2016) - [j43]Mehrbakhsh Nilashi, Dietmar Jannach, Othman bin Ibrahim, Mohammad Dalvi Esfahani, Hossein Ahmadi:
Recommendation quality, transparency, and website quality for trust-building in recommendation agents. Electron. Commer. Res. Appl. 19: 70-84 (2016) - [j42]Dietmar Jannach, Thomas Schmitz, Kostyantyn M. Shchekotykhin:
Parallel Model-Based Diagnosis on Multi-Core Computers. J. Artif. Intell. Res. 55: 835-887 (2016) - [j41]Dietmar Jannach, Michael Jugovac, Lukas Lerche:
Supporting the Design of Machine Learning Workflows with a Recommendation System. ACM Trans. Interact. Intell. Syst. 6(1): 8:1-8:35 (2016) - [c94]Dietmar Jannach, Sidra Naveed, Michael Jugovac:
User Control in Recommender Systems: Overview and Interaction Challenges. EC-Web 2016: 21-33 - [c93]Kostyantyn M. Shchekotykhin, Thomas Schmitz, Dietmar Jannach:
Efficient Sequential Model-Based Fault-Localization with Partial Diagnoses. IJCAI 2016: 1251-1257 - [c92]Sören Köcher, Dietmar Jannach, Michael Jugovac, Hartmut H. Holzmüller:
Investigating Mere-Presence Effects of Recommendations on the Consumer Choice Process. IntRS@RecSys 2016: 2-5 - [c91]Dietmar Jannach, Gediminas Adomavicius:
Recommendations with a Purpose. RecSys 2016: 7-10 - [c90]Thomas Schmitz, Birgit Hofer, Dietmar Jannach, Franz Wotawa:
Fragment-Based Diagnosis of Spreadsheets. STAF Workshops 2016: 372-387 - [c89]Iman Kamehkhosh, Dietmar Jannach, Lukas Lerche:
Personalized Next-Track Music Recommendation with Multi-dimensional Long-Term Preference Signals. UMAP (Extended Proceedings) 2016 - [c88]Lukas Lerche, Dietmar Jannach, Malte Ludewig:
On the Value of Reminders within E-Commerce Recommendations. UMAP 2016: 27-35 - [c87]Dietmar Jannach, Iman Kamehkhosh, Geoffray Bonnin:
Biases in Automated Music Playlist Generation: A Comparison of Next-Track Recommending Techniques. UMAP 2016: 281-285 - [c86]Thomas Schmitz, Dietmar Jannach:
Finding errors in the Enron spreadsheet corpus. VL/HCC 2016: 157-161 - 2015
- [j40]Dietmar Jannach, Lukas Lerche, Michael Jugovac:
Item Familiarity as a Possible Confounding Factor in User-Centric Recommender Systems Evaluation. i-com 14(1): 29-39 (2015) - [j39]Mehrbakhsh Nilashi, Dietmar Jannach, Othman bin Ibrahim, Norafida Ithnin:
Clustering- and regression-based multi-criteria collaborative filtering with incremental updates. Inf. Sci. 293: 235-250 (2015) - [j38]Hannes Werthner, Aurkene Alzua-Sorzabal, Lorenzo Cantoni, Astrid Dickinger, Ulrike Gretzel, Dietmar Jannach, Julia Neidhardt, Birgit Pröll, Francesco Ricci, Miriam Scaglione, Brigitte Stangl, Oliviero Stock, Markus Zanker:
Future research issues in IT and tourism. J. Inf. Technol. Tour. 15(1): 1-15 (2015) - [j37]Dietmar Jannach, Lukas Lerche, Iman Kamehkhosh, Michael Jugovac:
What recommenders recommend: an analysis of recommendation biases and possible countermeasures. User Model. User Adapt. Interact. 25(5): 427-491 (2015) - [c85]Dietmar Jannach, Thomas Schmitz, Kostyantyn M. Shchekotykhin:
Parallelized Hitting Set Computation for Model-Based Diagnosis. AAAI 2015: 1503-1510 - [c84]Dietmar Jannach, Thomas Schmitz:
Using Calculation Fragments for Spreadsheet Testing and Debugging. SEMS@ICSE 2015: 1-2 - [c83]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Thomas Schmitz:
MergeXplain: Fast Computation of Multiple Conflicts for Diagnosis. IJCAI 2015: 3221-3228 - [c82]Dietmar Jannach, Michael Jugovac, Lukas Lerche:
Adaptive Recommendation-based Modeling Support for Data Analysis Workflows. IUI 2015: 252-262 - [c81]Dietmar Jannach, Lukas Lerche, Iman Kamehkhosh:
Beyond "Hitting the Hits": Generating Coherent Music Playlist Continuations with the Right Tracks. RecSys 2015: 187-194 - [c80]Dietmar Jannach, Lukas Lerche, Michael Jugovac:
Adaptation and Evaluation of Recommendations for Short-term Shopping Goals. RecSys 2015: 211-218 - [c79]Dietmar Jannach, Lukas Lerche, Michael Jugovac:
Item Familiarity Effects in User-Centric Evaluations of Recommender Systems. RecSys Posters 2015 - [c78]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Thomas Schmitz:
A Divide-And-Conquer-Method for Computing Multiple Conflicts for Diagnosis. DX 2015: 3-10 - [e10]Heiner Stuckenschmidt, Dietmar Jannach:
E-Commerce and Web Technologies - 16th International Conference on Electronic Commerce and Web Technologies, EC-Web 2015, Valencia, Spain, September 2015, Revised Selected Papers. Lecture Notes in Business Information Processing 239, Springer 2015, ISBN 978-3-319-27728-8 [contents] - [e9]Dietmar Jannach, Jérôme Mengin, Bamshad Mobasher, Andrea Passerini, Paolo Viappiani:
Proceedings of the IJCAI 2015 Joint Workshop on Constraints and Preferences for Configuration and Recommendation and Intelligent Techniques for Web Personalization co-located with the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires, Argentina, July 27, 2015. CEUR Workshop Proceedings 1440, CEUR-WS.org 2015 [contents] - [r3]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Constraint-Based Recommender Systems. Recommender Systems Handbook 2015: 161-190 - [i2]Dietmar Jannach, Thomas Schmitz:
Using Calculation Fragments for Spreadsheet Testing and Debugging. CoRR abs/1503.03267 (2015) - 2014
- [j36]Geoffray Bonnin, Dietmar Jannach:
Automated Generation of Music Playlists: Survey and Experiments. ACM Comput. Surv. 47(2): 26:1-26:35 (2014) - [j35]Fatih Gedikli, Dietmar Jannach, Mouzhi Ge:
How should I explain? A comparison of different explanation types for recommender systems. Int. J. Hum. Comput. Stud. 72(4): 367-382 (2014) - [j34]Dietmar Jannach, Markus Zanker, Matthias Fuchs:
Leveraging multi-criteria customer feedback for satisfaction analysis and improved recommendations. J. Inf. Technol. Tour. 14(2): 119-149 (2014) - [j33]Dietmar Jannach, Thomas Schmitz, Birgit Hofer, Franz Wotawa:
Avoiding, finding and fixing spreadsheet errors - A survey of automated approaches for spreadsheet QA. J. Syst. Softw. 94: 129-150 (2014) - [j32]Gediminas Adomavicius, Dietmar Jannach:
Preface to the special issue on context-aware recommender systems. User Model. User Adapt. Interact. 24(1-2): 1-5 (2014) - [c77]Igor Vatolkin, Geoffray Bonnin, Dietmar Jannach:
Comparing Audio Features and Playlist Statistics for Music Classification. ECDA 2014: 437-447 - [c76]Dietmar Jannach, Simon Fischer:
Recommendation-based modeling support for data mining processes. RecSys 2014: 337-340 - [c75]Lukas Lerche, Dietmar Jannach:
Using graded implicit feedback for bayesian personalized ranking. RecSys 2014: 353-356 - [c74]Dietmar Jannach, Jill Freyne, Werner Geyer, Ido Guy, Andreas Hotho, Bamshad Mobasher:
The sixth ACM RecSys workshop on recommender systems and the social web. RecSys 2014: 395 - [c73]Dietmar Jannach, Iman Kamehkhosh, Geoffray Bonnin:
Analyzing the Characteristics of Shared Playlists for Music Recommendation. RSWeb@RecSys 2014 - [e8]Dietmar Jannach, Jill Freyne, Werner Geyer, Ido Guy, Andreas Hotho, Bamshad Mobasher:
Proceedings of the 6th Workshop on Recommender Systems and the Social Web (RSWeb 2014) co-located with the 8th ACM Conference on Recommender Systems (RecSys 2014), Foster City, CA, USA, October 6, 2014. CEUR Workshop Proceedings 1271, CEUR-WS.org 2014 [contents] - [r2]Fatih Gedikli, Dietmar Jannach:
Recommender Systems, Semantic-Based. Encyclopedia of Social Network Analysis and Mining 2014: 1501-1510 - [i1]Krzysztof Czarnecki, Arnaud Hubaux, Ethan Jackson, Dietmar Jannach, Tomi Männistö:
Unifying Product and Software Configuration (Dagstuhl Seminar 14172). Dagstuhl Reports 4(4): 20-35 (2014) - 2013
- [j31]Vikas Agrawal, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher W. Geib, Vibhav Gogate, Hans W. Guesgen, Dietmar Jannach, Michael Johanson, Kristian Kersting, George Dimitri Konidaris, Lars Kotthoff, Martin Michalowski, Sriraam Natarajan, Barry O'Sullivan, Marc Pickett, Vedran Podobnik, David Poole, Lokendra Shastri, Amarda Shehu, Gita Sukthankar:
The AAAI-13 Conference Workshops. AI Mag. 34(4): 9- (2013) - [j30]Dietmar Jannach, Lukas Lerche:
Perspektiven in der Offline-Evaluation von Empfehlungsalgorithmen. HMD Prax. Wirtsch. 293: 34-44 (2013) - [j29]Fatih Gedikli, Dietmar Jannach:
Improving recommendation accuracy based on item-specific tag preferences. ACM Trans. Intell. Syst. Technol. 4(1): 11:1-11:19 (2013) - [j28]Dietmar Jannach, Markus Zanker:
Modeling and Solving Distributed Configuration Problems: A CSP-Based Approach. IEEE Trans. Knowl. Data Eng. 25(3): 603-618 (2013) - [c72]Dietmar Jannach:
Toward Automatically Learned Search Heuristics for CSP-encoded Configuration Problems - Results from an Initial Experimental Analysis. Configuration Workshop 2013: 9-13 - [c71]Dietmar Jannach, Arash Baharloo, David Williamson:
Toward an Integrated Framework for Declarative and Interactive Spreadsheet Debugging. ENASE 2013: 117-124 - [c70]Geoffray Bonnin, Dietmar Jannach:
Evaluating The Quality of Generated Playlists Based on Hand-Crafted Samples. ISMIR 2013: 263-268 - [c69]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Jill Freyne, Andreas Hotho, Sarabjot Singh Anand, Ido Guy:
The fifth ACM RecSys workshop on recommender systems and the social web. RecSys 2013: 477-478 - [c68]Dietmar Jannach, Lukas Lerche, Fatih Gedikli, Geoffray Bonnin:
What Recommenders Recommend - An Analysis of Accuracy, Popularity, and Sales Diversity Effects. UMAP 2013: 25-37 - [e7]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Jill Freyne, Andreas Hotho, Sarabjot Singh Anand, Ido Guy:
Proceedings of the Fifth ACM RecSys Workshop on Recommender Systems and the Social Web co-located with the 7th ACM Conference on Recommender Systems (RecSys 2013), Hong Kong, China, October 13, 2013. CEUR Workshop Proceedings 1066, CEUR-WS.org 2013 [contents] - 2012
- [j27]Vikas Agrawal, Jorge A. Baier, Kostas E. Bekris, Yiling Chen, Artur S. d'Avila Garcez, Pascal Hitzler, Patrik Haslum, Dietmar Jannach, Edith Law, Freddy Lécué, Luís C. Lamb, Cynthia Matuszek, Héctor Palacios, Biplav Srivastava, Lokendra Shastri, Nathan R. Sturtevant, Roni Stern, Stefanie Tellex, Stavros Vassos:
Reports of the AAAI 2012 Conference Workshops. AI Mag. 33(4): 119- (2012) - [j26]Fernando López Hernández, Dietmar Jannach, José M. Martínez, Christian Timmerer, Narciso García, Hermann Hellwagner:
Bounded non-deterministic planning for multimedia adaptation. Appl. Intell. 36(1): 29-60 (2012) - [c67]Arnaud Hubaux, Dietmar Jannach, Conrad Drescher, Leonardo Murta, Tomi Männistö, Krzysztof Czarnecki, Patrick Heymans, Tien Nguyen, Markus Zanker:
Unifying Software, Product Configuration: A Research Roadmap. Configuration Workshop 2012: 31-35 - [c66]Dietmar Jannach, Markus Zanker, Mouzhi Ge, Marian Gröning:
Recommender Systems in Computer Science and Information Systems - A Landscape of Research. EC-Web 2012: 76-87 - [c65]Dietmar Jannach, Fatih Gedikli, Zeynep Karakaya, Oliver Juwig:
Recommending Hotels based on Multi-Dimensional Customer Ratings. ENTER 2012: 320-331 - [c64]Mouzhi Ge, Dietmar Jannach, Fatih Gedikli, Martin Hepp:
Effects of the Placement of Diverse Items in Recommendation Lists. ICEIS (2) 2012: 201-208 - [c63]Mouzhi Ge, Dietmar Jannach, Fatih Gedikli:
Bringing Diversity to Recommendation Lists - An Analysis of the Placement of Diverse Items. ICEIS 2012: 293-305 - [c62]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Andreas Hotho:
4th ACM RecSys workshop on recommender systems and the social web. RecSys 2012: 345-346 - [c61]Dietmar Jannach, Zeynep Karakaya, Fatih Gedikli:
Accuracy improvements for multi-criteria recommender systems. EC 2012: 674-689 - [e6]Bamshad Mobasher, Dietmar Jannach, Werner Geyer, Andreas Hotho:
Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web, RSWeb '12, Dublin, Ireland, September 9, 2012. ACM 2012, ISBN 978-1-4503-1638-5 [contents] - 2011
- [j25]Dietmar Jannach:
Progress and Challenges in Product Configuration Systems Development. IEEE Intell. Informatics Bull. 12(1): 6-7 (2011) - [j24]Fatih Gedikli, Mouzhi Ge, Dietmar Jannach:
Explaining Online Recommendations Using Personalized Tag Clouds. i-com 10(1): 3-10 (2011) - [c60]Dietmar Jannach, Lukas Kalabis:
Incremental Prediction of Configurator Input Values Based on Association Rules - A Case Study. Configuration Workshop 2011 - [c59]Mouzhi Ge, Markus Helfert, Dietmar Jannach:
Information quality assessment: validating measurement dimensions and processes. ECIS 2011: 75 - [c58]Fatih Gedikli, Mouzhi Ge, Dietmar Jannach:
Understanding Recommendations by Reading the Clouds. EC-Web 2011: 196-208 - [c57]Marius Kubatz, Fatih Gedikli, Dietmar Jannach:
LocalRank - Neighborhood-Based, Fast Computation of Tag Recommendations. EC-Web 2011: 258-269 - [c56]Mouzhi Ge, Fatih Gedikli, Dietmar Jannach:
Placing High-Diversity Items in Top-N Recommendation Lists. ITWP@IJCAI 2011 - [c55]Fatih Gedikli, Faruk Bagdat, Mouzhi Ge, Dietmar Jannach:
RF-Rec: Fast and Accurate Computation of Recommendations Based on Rating Frequencies. CEC 2011: 50-57 - [p4]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Developing Constraint-based Recommenders. Recommender Systems Handbook 2011: 187-215 - [e5]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Markus Zanker:
Proceedings of the IJCAI 2011 Workshop on Configuration, Barcelona, Spain, July 16, 2011. CEUR Workshop Proceedings 755, CEUR-WS.org 2011 [contents] - [e4]Sarabjot Singh Anand, Dietmar Jannach:
Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems, ITWP@IJCAI 2011, Barcelona, Spain, July 16, 2011. CEUR Workshop Proceedings 756, CEUR-WS.org 2011 [contents] - [e3]Bamshad Mobasher, Robin D. Burke, Dietmar Jannach, Gediminas Adomavicius:
Proceedings of the 2011 ACM Conference on Recommender Systems, RecSys 2011, Chicago, IL, USA, October 23-27, 2011. ACM 2011, ISBN 978-1-4503-0683-6 [contents] - 2010
- [b1]Dietmar Jannach, Markus Zanker, Alexander Felfernig, Gerhard Friedrich:
Recommender Systems - An Introduction. Cambridge University Press 2010, ISBN 978-0-521-49336-9, pp. I-XV, 1-335 - [j23]Jürgen Kuster, Dietmar Jannach, Gerhard Friedrich:
Applying Local Rescheduling in response to schedule disruptions. Ann. Oper. Res. 180(1): 265-282 (2010) - [j22]Markus Zanker, Francesco Ricci, Dietmar Jannach, Loren G. Terveen:
Measuring the impact of personalization and recommendation on user behaviour. Int. J. Hum. Comput. Stud. 68(8): 469-471 (2010) - [j21]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Gerhard Friedrich:
xCrawl: a high-recall crawling method for Web mining. Knowl. Inf. Syst. 25(2): 303-326 (2010) - [c54]Fatih Gedikli, Dietmar Jannach:
Recommending based on rating frequencies. RecSys 2010: 233-236 - [c53]Mouzhi Ge, Carla Delgado-Battenfeld, Dietmar Jannach:
Beyond accuracy: evaluating recommender systems by coverage and serendipity. RecSys 2010: 257-260 - [c52]Fatih Gedikli, Dietmar Jannach:
Neighborhood-restricted mining and weighted application of association rules for recommenders. ITWP@UMAP 2010 - [c51]Fatih Gedikli, Dietmar Jannach:
Recommending based on rating frequencies: Accurate enough? ITWP@UMAP 2010 - [c50]Fatih Gedikli, Dietmar Jannach:
Neighborhood-Restricted Mining and Weighted Application of Association Rules for Recommenders. WISE 2010: 157-165 - [e2]Bamshad Mobasher, Dietmar Jannach, Sarabjot Singh Anand:
Proceedings of the 8th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems, ITWP@UMAP 2010, Big Island, HI, USA, June 20, 2010. CEUR Workshop Proceedings 606, CEUR-WS.org 2010 [contents]
2000 – 2009
- 2009
- [j20]Dietmar Jannach:
Fast computation of query relaxations for knowledge-based recommenders. AI Commun. 22(4): 235-248 (2009) - [j19]Razvan C. Bunescu, Vitor R. Carvalho, Jan Chomicki, Vincent Conitzer, Michael T. Cox, Virginia Dignum, Zachary Dodds, Mark Dredze, David Furcy, Evgeniy Gabrilovich, Mehmet H. Göker, Hans W. Guesgen, Haym Hirsh, Dietmar Jannach, Ulrich Junker, Wolfgang Ketter, Alfred Kobsa, Sven Koenig, Tessa A. Lau, Lundy Lewis, Eric T. Matson, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Joelle Pineau, Pascal Poupart, Anita Raja, Wheeler Ruml, Norman M. Sadeh, Guy Shani, Daniel G. Shapiro, Sarabjot Singh Anand, Matthew E. Taylor, Kiri Wagstaff, Trey Smith, William E. Walsh, Rong Zhou:
AAAI 2008 Workshop Reports. AI Mag. 30(1): 108-118 (2009) - [j18]Alexander Felfernig, Gerhard Friedrich, Klaus Isak, Kostyantyn M. Shchekotykhin, Erich Teppan, Dietmar Jannach:
Automated debugging of recommender user interface descriptions. Appl. Intell. 31(1): 1-14 (2009) - [j17]Jürgen Kuster, Dietmar Jannach, Gerhard Friedrich:
Extending the RCPSP for modeling and solving disruption management problems. Appl. Intell. 31(3): 234-253 (2009) - [j16]Dietmar Jannach, Markus Zanker:
Recommender Systems in the Web 2.0 Sphere. IEEE Intell. Informatics Bull. 10(1): 4-5 (2009) - [j15]Dietmar Jannach, Markus Zanker, Matthias Fuchs:
Constraint-Based Recommendation in Tourism: A Multiperspective Case Study. J. Inf. Technol. Tour. 11(2): 139-155 (2009) - [j14]Dietmar Jannach, Kostyantyn M. Shchekotykhin, Gerhard Friedrich:
Automated ontology instantiation from tabular web sources - The AllRight system. J. Web Semant. 7(3): 136-153 (2009) - [c49]Kolja Hegelich, Dietmar Jannach:
Effectiveness of Different Recommender Algorithms in the Mobile Internet: A Case Study. ITWP 2009 - [c48]Dietmar Jannach, Kolja Hegelich:
A case study on the effectiveness of recommendations in the mobile internet. RecSys 2009: 205-208 - [c47]Dietmar Jannach, Werner Geyer, Casey Dugan, Jill Freyne, Sarabjot S. Anand, Bamshad Mobasher, Alfred Kobsa:
Workshop on recommender systems and the social web. RecSys 2009: 421-422 - [e1]Sarabjot S. Anand, Bamshad Mobasher, Alfred Kobsa, Dietmar Jannach:
Proceedings of the 7th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems (ITWP'09), Pasadena, California, USA, July 11-17, 2009 in conjunction with the 21st International Joint Conference on Artificial Intelligence - IJCAI 2009. CEUR Workshop Proceedings 528, CEUR-WS.org 2009 [contents] - 2008
- [j13]Dietmar Jannach, Markus Zanker, Joseph A. Konstan:
Special issue on Recommender Systems. AI Commun. 21(2-3): 95-96 (2008) - [c46]Markus Zanker, Dietmar Jannach, Marius-Calin Silaghi, Gerhard Friedrich:
A Distributed Generative CSP Framework for Multi-site Product Configuration. CIA 2008: 131-146 - [c45]Dietmar Jannach, Alexander Gut:
Exception Handling in Web Service Processes. The Evolution of Conceptual Modeling 2008: 225-253 - [c44]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Gerhard Friedrich:
xCrawl: A High-Recall Crawling Method for Web Mining. ICDM 2008: 550-559 - [c43]Dietmar Jannach:
Knowledge-based System Development with Scripting Technology: A Recommender System Example. SEKE 2008: 405-416 - [c42]Fernando López Hernández, Dietmar Jannach, José M. Martínez, Christian Timmerer, Hermann Hellwagner, Narciso García:
Multimedia Adaptation Decisions Modelled as Non-deterministic Operations. WIAMIS 2008: 46-49 - [p3]Jürgen Kuster, Dietmar Jannach:
Extending the Resource-Constrained Project Scheduling Problem for Disruption Management. Intelligent Techniques and Tools for Novel System Architectures 2008: 43-61 - [p2]Dietmar Jannach:
Finding Preferred Query Relaxations in Content-Based Recommenders. Intelligent Techniques and Tools for Novel System Architectures 2008: 81-97 - [r1]Dietmar Jannach, Christian Timmerer, Hermann Hellwagner:
Knowledge-Based Multimedia Adaptation Decision-Taking. Encyclopedia of Multimedia 2008: 391-394 - 2007
- [j12]Sarabjot Singh Anand, Daniel Bahls, Catherina Burghart, Mark H. Burstein, Huajun Chen, John Collins, Thomas G. Dietterich, Jon Doyle, Chris Drummond, William Elazmeh, Christopher W. Geib, Judy Goldsmith, Hans W. Guesgen, Jim Hendler, Dietmar Jannach, Nathalie Japkowicz, Ulrich Junker, Gal A. Kaminka, Alfred Kobsa, Jérôme Lang, David B. Leake, Lundy Lewis, Gerard Ligozat, Sofus A. Macskassy, Drew V. McDermott, Ted Metzler, Bamshad Mobasher, Ullas Nambiar, Zaiqing Nie, Klas Orsvärn, Barry O'Sullivan, David V. Pynadath, Jochen Renz, Rita V. Rodríguez, Thomas Roth-Berghofer, Stefan Schulz, Rudi Studer, Yimin Wang, Michael P. Wellman:
AAAI-07 Workshop Reports. AI Mag. 28(4): 119-128 (2007) - [j11]Markus Zanker, Markus Jessenitschnig, Dietmar Jannach, Sergiu Gordea:
Comparing Recommendation Strategies in a Commercial Context. IEEE Intell. Syst. 22(3): 69-73 (2007) - [j10]Dietmar Jannach, Klaus Leopold:
Knowledge-based multimedia adaptation for ubiquitous multimedia consumption. J. Netw. Comput. Appl. 30(3): 958-982 (2007) - [j9]Dietmar Jannach, Gerold Kreutler:
Rapid Development of Knowledge-Based Conversational Recommender Applications with Advisor Suite. J. Web Eng. 6(2): 165-192 (2007) - [c41]Jürgen Kuster, Dietmar Jannach, Gerhard Friedrich:
Local Rescheduling - A Novel Approach for Efficient Response to Schedule Disruptions. CISched 2007: 79-86 - [c40]Dietmar Jannach, Markus Zanker, Markus Jessenitschnig, Oskar Seidler:
Developing a Conversational Travel Advisor with ADVISOR SUITE. ENTER 2007: 43-52 - [c39]Dietmar Jannach, Uffe Bundgaard-Joergensen:
SAT: A Web-Based Interactive Advisor for Investor-Ready Business Plans. ICE-B 2007: 99-106 - [c38]Jürgen Kuster, Dietmar Jannach, Gerhard Friedrich:
Handling Alternative Activities in Resource-Constrained Project Scheduling Problems. IJCAI 2007: 1960-1965 - [c37]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Gerhard Friedrich:
Clustering web documents with tables for information extraction. K-CAP 2007: 169-170 - [c36]Kostyantyn M. Shchekotykhin, Dietmar Jannach, Gerhard Friedrich, Olga Kozeruk:
AllRight: Automatic Ontology Instantiation from Tabular Web Documents. ISWC/ASWC 2007: 466-479 - 2006
- [j8]Dietmar Jannach, Klaus Leopold, Christian Timmerer, Hermann Hellwagner:
A knowledge-based framework for multimedia adaptation. Appl. Intell. 24(2): 109-125 (2006) - [j7]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
An Integrated Environment for the Development of Knowledge-Based Recommender Applications. Int. J. Electron. Commer. 11(2): 11-34 (2006) - [c35]Markus Zanker, Marcel Bricman, Sergiu Gordea, Dietmar Jannach, Markus Jessenitschnig:
Persuasive Online-Selling in Quality and Taste Domains. EC-Web 2006: 51-60 - [c34]Dietmar Jannach, Markus Zanker:
Knowledge-Based Sales Advisory: Experiences and Future Directions. ICE-B 2006: 200-208 - [c33]Jürgen Kuster, Dietmar Jannach:
Handling Airport Ground Processes Based on Resource-Constrained Project Scheduling. IEA/AIE 2006: 166-176 - [c32]Dietmar Jannach, Johannes Liegl:
Conflict-Directed Relaxation of Constraints in Content-Based Recommender Systems. IEA/AIE 2006: 819-829 - [c31]Dietmar Jannach:
Techniques for Fast Query Relaxation in Content-Based Recommender Systems. KI 2006: 49-63 - [c30]Jürgen Kuster, Dietmar Jannach:
Approaches to Efficient Resource-Constrained Project Rescheduling. STAIRS 2006: 208-219 - 2005
- [c29]Dietmar Jannach, Gerold Kreutler:
Personalized User Preference Elicitation for e-Services. EEE 2005: 604-611 - 2004
- [j6]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner:
Consistency-based diagnosis of configuration knowledge bases. Artif. Intell. 152(2): 213-234 (2004) - [c28]Dietmar Jannach:
ADVISOR SUITE - A Knowledge-Based Sales Advisory-System. ECAI 2004: 720-724 - [c27]Dietmar Jannach, Gerold Kreutler:
Advisor Suite: A Tool for Rapid Development of Maintainable Online Sales Advisory Systems. ICWE 2004: 266-270 - [c26]Dietmar Jannach, Klaus Leopold, Hermann Hellwagner:
An Extensible Framework for Knowledge-Based Multimedia Adaptation. IEA/AIE 2004: 144-153 - [c25]Klaus Leopold, Dietmar Jannach, Hermann Hellwagner:
A knowledge and component based multimedia adaptation framework. ISMSE 2004: 10-17 - [c24]Dietmar Jannach, Gerold Kreutler:
Building on-line sales assistance systems with ADVISOR SUITE. SEKE 2004: 110-116 - [c23]Dietmar Jannach, Gerold Kreutler:
A Knowledge-Based Framework for the Rapid Development of Conversational Recommenders. WISE 2004: 390-402 - [c22]Dietmar Jannach, Klaus Leopold, Christian Timmerer, Hermann Hellwagner:
Toward Semantic Web Services for Multimedia Adaptation. WISE 2004: 641-652 - 2003
- [j5]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner, Markus Zanker:
Configuration knowledge representations for Semantic Web applications. Artif. Intell. Eng. Des. Anal. Manuf. 17(1): 31-50 (2003) - [j4]Liliana Ardissono, Alexander Felfernig, Gerhard Friedrich, Anna Goy, Dietmar Jannach, Giovanna Petrone, Ralph Schäfer, Markus Zanker:
A Framework for the Development of Personalized, Distributed Web-Based Configuration Systems. AI Mag. 24(3): 93-110 (2003) - [c21]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Christian Russ, Markus Zanker:
Developing Constraint-Based Applications with Spreadsheets. IEA/AIE 2003: 197-207 - [p1]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner, Markus Zanker:
Transforming UML Domain Descriptions into Configuration Knowledge Bases. Knowledge Transformation for the Semantic Web 2003: 154-168 - 2002
- [j3]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Christian Russ, Markus Zanker:
Multi-Site Product Configuration of Telecommunication switches. Int. J. Comput. 1(2): 101-107 (2002) - [c20]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Web-Based Configuration of Virtual Private Networks with Multiple Suppliers. AID 2002: 41-61 - [c19]Liliana Ardissono, Alexander Felfernig, Gerhard Friedrich, Anna Goy, Dietmar Jannach, Markus Meyer, Giovanna Petrone, Ralph Schäfer, Wilken Schuetz, Markus Zanker:
Personalising On-Line Configuration of Products and Services. ECAI 2002: 225-229 - [c18]Liliana Ardissono, Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker, Ralph Schäfer:
A Framework for Rapid Development of Advanced Web-based Configurator Applications. ECAI 2002: 618-622 - [c17]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner, Markus Zanker:
Acquiring Configuration Knowledge Bases in the Semantic Web Using UML. EKAW 2002: 352-357 - [c16]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner, Markus Zanker:
UML as knowledge acquisition frontend for Semantic Web configuration knowledge bases. RuleML 2002 - [c15]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Semantic Configuration Web Services in the CAWICOMS Project. ISWC 2002: 192-205 - [c14]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Configuration Knowledge Representation Using UML/OCL. UML 2002: 49-62 - 2001
- [j2]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach:
Conceptual modeling for configuration of mass-customizable products. Artif. Intell. Eng. 15(2): 165-176 (2001) - [c13]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Distributed Configuration as Distributed Dynamic Constraint Satisfaction. IEA/AIE 2001: 434-444 - [c12]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Intelligent Support for Interactive Configuration of Mass-Customized Products. IEA/AIE 2001: 746-756 - [c11]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner, Markus Zanker:
Hierarchical Diagnosis of Large Configurator Knowledge Bases. KI/ÖGAI 2001: 185-197 - [c10]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Towards Distributed Configuration. KI/ÖGAI 2001: 198-212 - [c9]Liliana Ardissono, Alexander Felfernig, Gerhard Friedrich, Anna Goy, Dietmar Jannach, Ralph Schäfer, Markus Zanker:
Web-based Commerce of Complex Products and Services with Multiple Suppliers. PuK 2001 - [c8]Liliana Ardissono, Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Ralph Schäfer, Markus Zanker:
Intelligent Interfaces for Distributed Web-Based Product and Service Configuration. Web Intelligence 2001: 184-188 - 2000
- [j1]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach:
Uml as Domain Specific Language for the Construction of Knowledge-Based Configuration Systems. Int. J. Softw. Eng. Knowl. Eng. 10(4): 449-469 (2000) - [c7]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner:
An Integrated Development Environment for The Design And Maintenance of Large Configuration Knowledge Bases. AID 2000: 169-189 - [c6]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Stumptner:
Consistency-Based Diagnosis of Configuration Knowledge Bases. ECAI 2000: 146-150 - [c5]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Integrating Knowledge-Based Configuration Systems by Sharing Functional Architectures. EKAW 2000: 312-327 - [c4]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
Cooperating Configuration Agents Supporting Supply Chain Integration of Customizable Products. ICMAS 2000: 385-386 - [c3]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach, Markus Zanker:
A Framework for the Development of Cooperative Configuration Agents. IEA/AIE 2000: 24-33 - [c2]Alexander Felfernig, Dietmar Jannach, Markus Zanker:
Contextual Diagrams as Structuring Mechanisms for Designing Configuration Knowledge Bases in UML. UML 2000: 240-254
1990 – 1999
- 1999
- [c1]Alexander Felfernig, Gerhard Friedrich, Dietmar Jannach:
Knowledge Acquisition for Configuration Systems: UML as a link between AI and Software Engineering. PuK 1999
Coauthor Index
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