Thi Ngoc Trang Tran - Publications

Below you will find a selection of my peer-reviewed publications (listed in reverse chronological order). I have authored and co-authored more than 80 peer-reviewed papers published in high-impact journals such as UMUAI, Foundations and Trends® in Information Retrieval, ACM TIIS, and JIIS, as well as in leading international conferences including AAAI, IJCAI, ICSE, UMAP, and RecSys. According to Google Scholar (as of 26 February 2026), my work has received 2,159 citations, with an h-index of 21, and my most cited publication has accumulated 386 citations. In addition, I am the main or co-author of three papers that received Best Paper Awards at the Configuration Workshops (CWS 2016 and CWS 2018) and SEKE 2017.

Further details and my complete publication record are available on Google Scholar and DBLP.

Journal papers

[JIIS 2024] A. Felfernig, M. Wundara, T. N. T. Tran, V. M. Le, S. Lubos, and S. Polat-Erdeniz (2024). Sports recommender systems: overview and research directions, Journal of Intelligent Information Systems. https://doi.org/10.1007/s10844-024-00857-w
[FBD 2024] M. Uta, A. Felfernig, V.M. Le, T. N. T. Tran, D. Garber, S. Lubos, and T. Burgstaller (2024). Knowledge-based Recommender Systems: Overview and Research Directions. Frontiers in Big Data, section Recommender Systems. https://doi.org/10.3389/fdata.2024.1304439
[FBD 2024] A. Felfernig, M. Wundara, T. N. T. Tran, S. Polat-Erdeniz, S. Lubos, M. El-Mansi, D. Garber, and V. M. Le (2023). Recommender Systems for Sustainability: Overview and Research Issues. Frontiers in Big Data, section Recommender Systems. https://doi.org/10.3389/fdata.2023.1284511
[UMUAI 2023] T. N. T. Tran, A. Felfernig, and V. M. Le (2023). An Overview of Consensus Models for Group Decision-Making and Group Recommender Systems. Journal of User Modeling and User-Adapted Interaction. https://doi.org/10.1007/s11257-023-09380-z
[CDBE 2022] S. P. Erdeniz, S.P.K. Veeranki, S. Jauk, T. N. T. Tran, A. Felfernig, M. Schrempf, D. Kramer, and W. Leodolter (2022). Explaining Predictions of Decision Support Systems in Healthcare. Current Directions in Biomedical Engineering, vol. 8, no. 2, pp. 117-120. https://doi.org/10.1515/cdbme-2022-1031
[FTIR 2021] ] E. Lex, D. Kowald, P. Seitlinger, T. N. T. Tran, A. Felfernig, and M. Schedl (2021). Psychology informed Recommender Systems. Foundations and Trends® in Information Retrieval, vol. 15, no. 2, pp 134-242. http://dx.doi.org/10.1561/1500000090
[ACM_TIIS 2021] T. N. T. Tran, A. Felfernig, and N. Tintarev (2021). Humanized Recommender Systems: State-of-the-art and Research Issues. ACM Transactions on Interactive Intelligent Systems, vol. 11, no. 2, article 9, pp. 1-41. https://doi.org/10.1145/3446906
[SI 2021] V. M. Le, A. Felfernig, T. N. T. Tran, M. Atas, M. Uta, D. Benavides, and J. Galindo (2021). DirectDebug: A Software Package for the Automated Testing and Debugging of Feature Models. Software Impacts, 100085, vol. 9. https://doi.org/10.1016/j.simpa.2021.100085
[JIIS 2021] M. Atas, A. Felfernig, S. Polat-Erdeniz, A. Popescu, T. N. T. Tran, and M. Uta (2021). Towards psychology-aware preference construction in recommender systems: Overview and research issues. Journal of Intelligent Information Systems. https://doi.org/10.1007/s10844-021-00674-5
[JIIS 2020] T. N. T. Tran, A. Felfernig, C. Trattner, and A. Holzinger (2020). Recommender systems in the healthcare domain: state-of-the-art and research issues. Journal of Intelligent Information Systems. https://doi.org/10.1007/s10844-020-00633-6
[JUCS 2020] T. N. T. Tran, M. Atas, V.M. Le, R. Samer, and M. Stettinger (2020). Social Choice-based Explanations: An Approach to Enhancing Fairness and Consensus Aspects. Journal of Universal Computer Science, vol. 26, no. 3, pp. 402-431.
[ES 2019] S. Polat-Erdeniz, A. Menychtas, I. Maglogiannis, A. Felfernig, and T. N. T. Tran (2019). Recommender systems for IoT enabled quantified-self applications. Evolving Systems, vol. 11, pp. 291-304. https://doi.org/10.1007/s12530-019-09302-8
[JIIS 2018] T. N. T. Tran, M. Atas, A. Felfernig, and M. Stettinger (2018). An Overview of Recommender Systems in the Healthy Food Domain. Journal of Intelligent Information Systems (JIIS), vol. 50, pp. 501-526. https://doi.org/10.1007/s10844-017-0469-0

Conference papers

[RecSys 2024] T. N. T. Tran, S. P. Erdeniz, A. Felfernig, S. Lubos, M. E. Mansi, and V. M. Le (2024). Less is More: Towards Sustainability-Aware Persuasive Explanations in Recommender Systems, In Proceedings of the 18th ACM Conference on Recommender Systems - RecSys 2024. Association for Computing Machinery (ACM). https://doi.org/10.1145/3640457.3691708
[UMAP 2024] S. Lubos, T. N. T. Tran, A. Felfernig, S. P. Erdeniz, and V. M. Le (2024). LLM-generated Explanations for Recommender Systems, UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery (ACM). https://doi.org/10.1145/3631700.36651
[Re@Next 2024] S. Lubos, A. Felfernig, T. N. T. Tran, D. Garber, M.E. Mansi, S.P. Erdeniz, and V. M. Le (2024). Leveraging LLMs for the Quality Assurance of Software Requirements. In 32nd IEEE International Requirements Engineering 2024, RE@Next! Track, (RE@Next! 2024), Reykjavik, Iceland. doi: 10.1109/RE59067.2024.00046
[AAAI 2024] V. M. Le, A. Felfernig, T. N. T. Tran, and M. Uta (2024). InformedQX: Informed Conflict Detection for Over-Constrained Problems. In 38th AAAI Conference on Artificial Intelligence. AAAI’24, Vancouver, Canada. https://doi.org/10.1609/aaai.v38i9.28932
[PAIS 2023] T. Burgstaller, V. M. Le, T. N. T. Tran, and A. Felfernig (2023). FMTesting: A FeatureIDE Plug-in for Automated Feature Model Analysis and Diagnosis. In 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), Kraków, Poland. DOI: 10.3233/FAIA230640
[SPLC 2023] S. Lubos, A. Felfernig, V. M. Le, T. N. T. Tran, D. Benavides, J.A. Zamudio, and D. Garber (2023). Analysis Operations On The Run: Feature Model Analysis in Constraint-based Recommender Systems. In 27th ACM International Systems and Software Product Line Conference (SPLC 2023), Tokyo, Japan. https://doi.org/10.1145/3579027.3608982
[UMAP 2023] T. N. T. Tran, A. Felfernig, V. M. Le, T.M.N. Chau, and T.G. Mai (2023). User Needs for Explanations of Recommendations: In-depth Analyses of the Role of Item Domain and Personal Characteristics. In 31st ACM Conference on User Modelling, Adaptation and Personalization. ACM UMAP 2023, Limassol, Cyprus. https://doi.org/10.1145/3565472.3592950
[AAAI 2023] V. M. Le, C.V. Silva, A. Felfernig, T. N. T. Tran, J. Galindo, and D. Benavides (2023). FastDiagP: An Algorithm for Parallelized Direct Diagnosis. In 37th AAAI Conference on Artificial Intelligence. AAAI’23, Washington, DC, USA. https://doi.org/10.1609/aaai.v37i5.25792
[SPLC 2022] V. M. Le, A. Felfernig, M. Uta, T. N. T. Tran, and C. Vidal-Silva (2022). WipeOutR: Automated Redundancy Detection for Feature Models. In 26th ACM International Systems and Software Product Line Conference – Volume A (SPLC’22), Graz, Austria. https://doi.org/10.1145/3546932.3546992
[RecSys_LBR_2021] T. N. T. Tran, V. M. Le, M. Atas, A. Felfernig, M. Stettinger, and A. Popescu (2021). Do Users Appreciate Explanations of Recommendations? An Analysis in the Movie Domain. In the RecSys 2021 Late-Breaking Results, pp. 645-650, Virtual. https://doi.org/10.1145/3460231.3478859
[SPLC 2021] M. Uta, A. Felfernig, V. M. Le, A. Popescu, T. N. T. Tran, and D. Helic (2021). Evaluating Recommender Systems in Feature Model Configuration. In the 25th ACM International Systems and Software Product Line Conference (SPLC 2021), pp.58-63, Virtual. https://doi.org/10.1145/3461001.3471144
[ICSE_NIER 2021] V. M. Le, A. Felfernig, M. Uta, D. Benavides, J. Galindo, and T. N. T. Tran (2021). DirectDebug: Automated Testing and Debugging of Feature Models. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER), pp. 81-85, IEEE/ACM, Virtual. https://doi.org/10.1109/ICSE-NIER52604.2021.00025
[ISMIS 2020] V. M. Le, T. N. T. Tran, and A. Felfernig (2021). A Conversion of Feature Models into an Executable Representation in Microsoft Excel. In: Stettinger M., Leitner G., Felfernig A., Ras Z.W. (eds) Intelligent Systems in Industrial Applications (pp. 153-168). ISMIS 2020, Graz, Austria. Studies in Computational Intelligence, vol 949. https://doi.org/10.1007/978-3-030-67148-8_12
[ECAI 2020] M. Stettinger, T. N. T. Tran, I. Pribik, G. Leitner, A. Felfernig, R. Samer, M. Atas, and M. Wundara (2020). KNOWLEDGECHECKR: Intelligent Techniques for Counteracting Forgetting. In: G. DeGiacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarin, J. Lang (eds.) 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostela, Spain, vol. 325, pp. 3034-3039, Frontiers in Artificial Intelligence and Applications. IOS Press. https://doi.org/10.3233/FAIA200479
[UMAP 2019] M. Atas, R. Samer, A. Felfernig, T. N. T. Tran, S. P. Erdeniz, and M. Stettinger. 2019. Socially-Aware Diagnosis for Constraint-Based Recommendation. In Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP '19). Association for Computing Machinery, New York, NY, USA, 121–129. https://doi.org/10.1145/3320435.3320436
[IEA_AIE 2019] M. Atas, T. N. T. Tran, A. Felfernig, S. Polat Erdeniz, R. Samer, and M. Stettinger (2019). Towards Similarity-Aware Constraint-Based Recommendation. In: Wotawa F., Friedrich G., Pill I., Koitz-Hristov R., Ali M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2019), Graz, Austria. Lecture Notes in Computer Science, vol 11606, pp. 287-299. Springer. https://doi.org/10.1007/978-3-030-22999-3_26
[UMAP 2019] T. N. T. Tran, M. Atas, A. Felfernig, V. M. Le, R. Samer, and M. Stettinger (2019). Towards Social Choice-based Explanations in Group Recommender Systems. In Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (UMAP ’19), Larnaca, Cyprus, pp. 13-21. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3320435.3320437
[UMAP_LBR_2019] T. N. T. Tran, A. Felfernig, V. M. Le, M. Atas, M. Stettinger, and R. Samer (2019). User Interfaces for Counteracting Decision Manipulation in Group Recommender Systems. In Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization (UMAP’19 Adjunct), pp. 93-98, Larnaca, Cyprus. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3314183.3324977
[UMAP_2018] T. N. T. Tran, M. Atas, A. Felfernig, R. Samer, and M. Stettinger (2018). Investigating Serial Position Effects in Sequential Group Decision Making. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP ’18), Singapore, pp. 239-243. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3209219.3209255
[UMAP_2018] M. Atas, S. Reiterer, A. Felfernig, T. N. T. Tran, and M. Stettinger (2018). Polarization Effects in Group Decisions. In Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP ’18), Singapore, pp. 305-310. Association for Computing Machinery, New York, NY, USA, 305–310. https://doi.org/10.1145/3213586.3225242
[IEA_AIE 2018] M. Atas, T. N. T. Tran, A. Felfernig, and R. Samer (2018). Socially-aware Recommendation for Over-Constrained Problems. In: Mouhoub M., Sadaoui S., Ait Mohamed O., Ali M. (eds) Recent Trends and Future Technology in Applied Intelligence. 31st International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE 2018), Montreal, Canada. Lecture Notes in Computer Science, vol 10868, pp. 267-278. Springer. https://doi.org/10.1007/978-3-319-92058-0_25

Workshop papers

[IntRS 2025] S. Lubos, T. N. T. Tran, V. M. Le, D. Garber, M. Henrich, RR. Willfort, and J. Fuchs (2025). Towards LLM-Enhanced Group Recommender Systems, In Proceedings of Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, September 22, 2025, Prague - IntRS’25, https://ceur-ws.org/Vol-4027/paper5.pdf
[RecSoGood 2025] A. Felfernig, D. Garber., V. M. Le, S. Lubos, and T. N. T. Tran (2025). Sustainability Evaluation Metrics for Recommender Systems, In L. Boratto, F. M. Malloci, A. De Filippo, E. Lex, N. Mauro, & F. Ricci (Hrsg.), Recommender Systems for Sustainability and Social Good - Second International Workshop, RecSoGood 2025, Proceedings (S. 14–26). (Communications in Computer and Information Science; Band 2802 CCIS). https://doi.org/10.1007/978-3-032-13342-7_2

[ECAI 2025] A. Felfernig, D. Garber, V. M. Le, S. Lubos, and T. N. T. Tran (2025). Towards LLM-Enhanced Product Line Scoping. In Proceedings of the 27th International Workshop on Configuration (ConfWS 2025) co-located with the 28th European Conference on Artificial Intelligence (ECAI 2025) (Band 4149, S. 128-134). CEUR Workshop Proceedings. https://ceur-ws.org/Vol-4149/paper11.pdf
[IntRS 2025] S. Lubos, A. Felfernig, D. Garber, V. M. Le, and T. N. T. Tran (2025). Towards LLM-Based Usability Analysis for Recommender User Interfaces. In 12th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’25 Workshop @ RecSys 2025) (Band 4027). CEUR Workshop Proceedings. https://ceur-ws.org/Vol-4027/paper7.pdf
[MABM 2023] S.P. Erdeniz, T. N. T. Tran, A. Felfernig, D. Kramer, M. Schrempf, and P. Rainer (2023). Employing Nudge Theory and Persuasive Principles with Explainable AI in Clinical Decision Support. Workshop on Machine Learning and Artificial Intelligence in Bioinformatics and Medical Informatics (MABM 2023), in conjunction with the 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2023), Istanbul, Turkey. doi: 10.1109/BIBM58861.2023.10385315.
[IntRS 2023] S. Lubos, T. N. T. Tran, S.P. Erdeniz, M.E. Mansi, A. Felfernig, M. Wundara, and G. Leitner (2023). Concentrating on Impact: Consequence-based Explanations in Recommender Systems. In 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’23), co-located with 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore. https://ceur-ws.org/Vol-3534/paper5.pdf
[ConfWS 2023] D. Garber, T. Burgstaller, A. Felfernig, V. M. Le, S. Lubos, T. N. T. Tran, and S. Polat-Erdeniz (2023). Collaborative Recommendation of Search Heuristics. In 25th International Workshop on Configuration (ConfWS 2023), Malaga, Spain. https://ceur-ws.org/Vol-3509/paper6.pdf
[IntRS 2022] B. Gjergjizi, T. N. T. Tran, and A. Felfernig (2022). The Impacts of Primacy/Recency Effects on Item Review Sentiment Analysis. In Proceedings of the 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2022), Hybrid Event, Seattle, USA. https://ceur-ws.org/Vol-3222/paper3.pdf
[SPLC 2022] V. M. Le, T. N. T. Tran, and A. Felfernig (2022). Consistency-based Integration of Multi-Stakeholder Recommender Systems With Feature Model Configuration. In 26th ACM International Systems and Software Product Line Conference – Volume B (SPLC’22), Graz, Austria. https://doi.org/10.1145/3503229.3547050
[SPLC 2022] V. M. Le, A. Felfernig, and T. N. T. Tran (2022). Test Case Aggregation for Efficient Feature Model Testing. In 26th ACM International Systems and Software Product Line Conference – Volume B (SPLC’22), Graz, Austria. https://doi.org/10.1145/3503229.3547046
[IntRS 2021] T. N. T. Tran, C.I. Baumann, A. Felfernig, and V. M. Le (2021). The Immunity of Users’ Item Selection from Serial Position Effects in Multi-Attribute Item Recommendation Scenarios. In Proceedings of RecSys’21 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’21), Amsterdam, Netherlands, pp. 101-111. https://ceur-ws.org/Vol-2948/short2.pdf
[ConfWS 2021] V. M. Le, T. N. T. Tran, M. Stettinger, L. Weißl, A. Felfernig, M. Atas, S.P. Erdeniz, and A. Popescu (2021). Counteracting Exam Cheating by Leveraging Configuration and Recommendation Techniques. In Proceedings of the 23rd International Configuration Workshop, Vienna, Austria, pp. 73-80. https://ceur-ws.org/Vol-2945/53-VML-ConfWS21_paper_7.pdf
[ConfWS 2020] A. Felfernig, V. M. Le, and T. N. T. Tran (2020). Supporting Feature Model-Based Configuration in Microsoft Excel. In Proceedings of the 22nd International Configuration Workshop, Vicenza, Italy, pp. 35-38.
[ConfWS 2018] M. Atas, T. N. T. Tran, R. Samer, A. Felfernig, and M. Stettinger (2018). Liquid Democracy in Group-based Configuration. In Proceedings of the 20th International Configuration Workshop, Graz, Austria, pp. 93-98. https://ceur-ws.org/Vol-2220/15_CONFWS18_paper_32.pdf (ConfWS'18 Best Paper Award)
[RS-BDA 2016] T. N. T. Tran, M. Atas, M. Stettinger, and A. Felfernig (2016). An extension of CHOICLA User Interfaces for Configurable Products. In the 2nd Workshop on Recommender Systems and Big Data Analytics (RS-BDA’16), Graz, Austria, pp. 1-4.
[ConfWS 2016] A. Felfernig, M. Atas, T. N. T. Tran, and M. Stettinger (2016). Towards Group-based Configuration. In Proceedings of the 18th International Configuration Workshop, Toulouse, France, pp. 69-72. (ConfWS’16 Runner-up Best Paper Award).
[SEKE 2017] A. Felfernig, A. Shehadeh, M. Jeran, C. Gütl, T. N. T. Tran, M. Atas, S. Polat Eredeniz, M. Stettinger, A. Akcay, and S. Reiterer (2016). StudyBattles: A Learning Environment for Knowledge-based Configuration. In Proceedings of the 18th International Configuration Workshop, Toulouse, France, pp. 109-116. (SEKE'17 Best Paper Award)

Book chapters

A. Felfernig, T. N. T. Tran, and V. M. Le (2021). Recommender Systems Beyond E-Commerce: Presence and Future. In: T. Dutta, M.K. Mandal (Eds.), Consumer Happiness: Multiple Perspectives. Studies in Rhythm Engineering. Springer, Singapore.
A. Felfernig, M. Atas, D. Helic, T. N. T. Tran, M. Stettinger, and R. Samer (2018). Algorithms for Group Recommendation. In A. Felfernig, L. Boratto, M. Stettinger, and M. Tkalcic (Eds.), Group Recommender Systems: An Introduction (pp. 27-58). SpringerBriefs in Electrical and Computer Engineering. Springer.
A. Felfernig, M. Atas, M. Stettinger, T. N. T. Tran, and S. Reiterer (2018). Group Recommender Applications. In A. Felfernig, L. Boratto, M. Stettinger, and M. Tkalcic (Eds.), Group Recommender Systems: An Introduction (pp. 75-89). SpringerBriefs in Electrical and Computer Engineering. Springer.
A. Felfernig, N. Tintarev, T. N. T. Tran, and M. Stettinger (2018). Explanations for Groups. In A. Felfernig, L. Boratto, M. Stettinger, and M. Tkalcic (Eds.), Group Recommender Systems: An Introduction (pp. 105-126). SpringerBriefs in Electrical and Computer Engineering. Springer.
A. Felfernig, M. Atas, R. Samer, M. Stettinger, T. N. T. Tran, and S. Reiterer (2018). Further Choice Scenarios. In A. Felfernig, L. Boratto, M. Stettinger, and M. Tkalcic (Eds.), Group Recommender Systems: An Introduction (pp. 129-144). SpringerBriefs in Electrical and Computer Engineering. Springer.
A. Felfernig, M. Atas, M. Stettinger, T. N. T. Tran, and G. Leitner (2018). Biases in Group Decisions. In A. Felfernig, L. Boratto, M. Stettinger, and M. Tkalcic (Eds.), Group Recommender Systems: An Introduction (pp. 145-155). SpringerBriefs in Electrical and Computer Engineering. Springer.

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