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ORCIDNava Tintarev
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- affiliation: Maastricht University, The Netherlands
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2020 – today
- 2024
[j21]Nava Tintarev
, Bart P. Knijnenburg, Martijn C. Willemsen:
Measuring the benefit of increased transparency and control in news recommendation. AI Mag. 45(2): 212-226 (2024)- [j20]Alisa Rieger, Tim Draws, Mariët Theune, Nava Tintarev:
Nudges to Mitigate Confirmation Bias during Web Search on Debated Topics: Support vs. Manipulation. ACM Trans. Web 18(2): 27:1-27:27 (2024) - [j19]Francesco Barile, Tim Draws, Oana Inel, Alisa Rieger, Shabnam Najafian, Amir Ebrahimi Fard, Rishav Hada, Nava Tintarev:
Evaluating explainable social choice-based aggregation strategies for group recommendation. User Model. User Adapt. Interact. 34(1): 1-58 (2024) - [j18]Shabnam Najafian, Geoff Musick, Bart P. Knijnenburg, Nava Tintarev:
How do people make decisions in disclosing personal information in tourism group recommendations in competitive versus cooperative conditions? User Model. User Adapt. Interact. 34(3): 549-581 (2024) - [c86]Aashutosh Ganesh, Mirela Popa, Daan Odijk, Nava Tintarev:
Does spatio-temporal information benefit the video summarization task? AEQUITAS@ECAI 2024 - [c85]Johannes Kruse, Lien Michiels, Alain Starke, Nava Tintarev, Sanne Vrijenhoek:
NORMalize: A Tutorial on the Normative Design and Evaluation of Information Access Systems. CHIIR 2024: 422-424 - [c84]Federico Maria Cau, Nava Tintarev:
Navigating the Thin Line: Examining User Behavior in Search to Detect Engagement and Backfire Effects. ECIR (4) 2024: 403-419 - [c83]Alain Starke, Sanne Vrijenhoek, Lien Michiels, Johannes Kruse, Nava Tintarev:
NORMalize 2024: The Second Workshop on Normative Design and Evaluation of Recommender Systems. RecSys 2024: 1242-1244 - [c82]Francesco Barile, Federico Maria Cau, Nava Tintarev:
A Preliminary Analysis on Self and Peer Evaluation of Personality Models for Recommender Systems. UMAP (Adjunct Publication) 2024 - [c81]Francesco Barile, Federico Maria Cau, Nava Tintarev:
A Preliminary Study of the Impact of Personality on Satisfaction in Group Contexts. UMAP (Adjunct Publication) 2024 - [e11]Lien Michiels, Johannes Kruse, Jordi Viader Guerrero, Nava Tintarev:
Proceedings of the First Workshop on the Normative Design and Evaluation of Recommender Systems (NORMalize 2023) co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 19, 2023. CEUR Workshop Proceedings 3639, CEUR-WS.org 2024 [contents] - [i18]Federico Maria Cau, Nava Tintarev:
Navigating the Thin Line: Examining User Behavior in Search to Detect Engagement and Backfire Effects. CoRR abs/2401.11201 (2024) - [i17]Roan Schellingerhout, Francesco Barile, Nava Tintarev:
Creating Healthy Friction: Determining Stakeholder Requirements of Job Recommendation Explanations. CoRR abs/2409.15971 (2024) - [i16]Dina Zilbershtein, Francesco Barile, Daan Odijk, Nava Tintarev:
Bridging the Transparency Gap: Exploring Multi-Stakeholder Preferences for Targeted Advertisement Explanations. CoRR abs/2409.15998 (2024) - [i15]Aashutosh Ganesh, Mirela Popa, Daan Odijk, Nava Tintarev:
Does SpatioTemporal information benefit Two video summarization benchmarks? CoRR abs/2410.03323 (2024) - 2023
- [j17]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) - [j16]Federico Maria Cau, Hanna Hauptmann, Lucio Davide Spano, Nava Tintarev:
Effects of AI and Logic-Style Explanations on Users' Decisions Under Different Levels of Uncertainty. ACM Trans. Interact. Intell. Syst. 13(4): 22:1-22:42 (2023) - [c80]Mireia Yurrita, Tim Draws, Agathe Balayn, Dave Murray-Rust, Nava Tintarev, Alessandro Bozzon:
Disentangling Fairness Perceptions in Algorithmic Decision-Making: the Effects of Explanations, Human Oversight, and Contestability. CHI 2023: 134:1-134:21 - [c79]Alisa Rieger, Frank Bredius, Nava Tintarev, Maria Soledad Pera:
Searching for the Whole Truth: Harnessing the Power of Intellectual Humility to Boost Better Search on Debated Topics. CHI Extended Abstracts 2023: 248:1-248:8 - [c78]Tim Draws, Karthikeyan Natesan Ramamurthy, Ioana Baldini, Amit Dhurandhar, Inkit Padhi, Benjamin Timmermans, Nava Tintarev:
Explainable Cross-Topic Stance Detection for Search Results. CHIIR 2023: 221-235 - [c77]Adarsa Sivaprasad, Ehud Reiter, Nava Tintarev, Nir Oren:
Evaluation of Human-Understandability of Global Model Explanations Using Decision Tree. ECAI Workshops (1) 2023: 43-65 - [c76]Tim Draws, Nirmal Roy, Oana Inel, Alisa Rieger, Rishav Hada, Mehmet Orcun Yalcin, Benjamin Timmermans, Nava Tintarev:
Viewpoint Diversity in Search Results. ECIR (1) 2023: 279-297 - [c75]Federico Maria Cau, Hanna Hauptmann, Lucio Davide Spano, Nava Tintarev:
Supporting High-Uncertainty Decisions through AI and Logic-Style Explanations. IUI 2023: 251-263 - [c74]Sanne Vrijenhoek, Lien Michiels, Johannes Kruse, Alain Starke, Nava Tintarev, Jordi Viader Guerrero:
NORMalize: The First Workshop on Normative Design and Evaluation of Recommender Systems. RecSys 2023: 1252-1254 - [c73]Rishav Hada, Amir Ebrahimi Fard, Sarah Shugars, Federico Bianchi, Patrícia G. C. Rossini, Dirk Hovy, Rebekah Tromble, Nava Tintarev:
Beyond Digital "Echo Chambers": The Role of Viewpoint Diversity in Political Discussion. WSDM 2023: 33-41 - [c72]Zhangyi Wu, Tim Draws, Federico Cau, Francesco Barile, Alisa Rieger, Nava Tintarev:
Explaining Search Result Stances to Opinionated People. xAI (2) 2023: 573-596 - [c71]Roan Schellingerhout, Francesco Barile, Nava Tintarev:
A Co-design Study for Multi-stakeholder Job Recommender System Explanations. xAI (2) 2023: 597-620 - [i14]Roan Schellingerhout, Francesco Barile, Nava Tintarev:
A Co-design Study for Multi-Stakeholder Job Recommender System Explanations. CoRR abs/2309.05507 (2023) - [i13]Zhangyi Wu, Tim Draws, Federico Cau, Francesco Barile, Alisa Rieger, Nava Tintarev:
Explaining Search Result Stances to Opinionated People. CoRR abs/2309.08460 (2023) - [i12]Adarsa Sivaprasad, Ehud Reiter, Nava Tintarev, Nir Oren:
Evaluation of Human-Understandability of Global Model Explanations using Decision Tree. CoRR abs/2309.09917 (2023) - 2022
- [j15]Tommaso Di Noia, Nava Tintarev, Panagiota Fatourou, Markus Schedl:
Recommender systems under European AI regulations. Commun. ACM 65(4): 69-73 (2022) - [c70]Tim Draws, Oana Inel, Nava Tintarev, Christian Baden, Benjamin Timmermans:
Comprehensive Viewpoint Representations for a Deeper Understanding of User Interactions With Debated Topics. CHIIR 2022: 135-145 - [c69]Federico Bianchi, Stefanie Anja Hills, Patrícia G. C. Rossini, Dirk Hovy, Rebekah Tromble, Nava Tintarev:
"It's Not Just Hate": A Multi-Dimensional Perspective on Detecting Harmful Speech Online. EMNLP 2022: 8093-8099 - [c68]Alisa Rieger, Qurat-ul-ain Shaheen, Carles Sierra, Mariët Theune, Nava Tintarev:
Towards Healthy Engagement with Online Debates: An Investigation of Debate Summaries and Personalized Persuasive Suggestions. UMAP (Adjunct Publication) 2022: 192-199 - [r2]Nava Tintarev, Judith Masthoff:
Beyond Explaining Single Item Recommendations. Recommender Systems Handbook 2022: 711-756 - [i11]Federico Bianchi, Stefanie Anja Hills, Patrícia G. C. Rossini, Dirk Hovy, Rebekah Tromble, Nava Tintarev:
"It's Not Just Hate": A Multi-Dimensional Perspective on Detecting Harmful Speech Online. CoRR abs/2210.15870 (2022) - [i10]Rishav Hada, Amir Ebrahimi Fard, Sarah Shugars, Federico Bianchi, Patrícia G. C. Rossini, Dirk Hovy, Rebekah Tromble, Nava Tintarev:
Beyond Digital "Echo Chambers": The Role of Viewpoint Diversity in Political Discussion. CoRR abs/2212.09056 (2022) - 2021
- [j14]Abraham Bernstein, Claes H. de Vreese, Natali Helberger, Wolfgang Schulz, Katharina Anna Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Möller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, Theresa Zueger:
Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482). Dagstuhl Manifestos 9(1): 43-61 (2021) - [j13]Oana Inel, Tomislav Duricic, Harmanpreet Kaur, Elisabeth Lex, Nava Tintarev:
Design Implications for Explanations: A Case Study on Supporting Reflective Assessment of Potentially Misleading Videos. Frontiers Artif. Intell. 4: 712072 (2021) - [j12]Tim Draws, Nava Tintarev, Ujwal Gadiraju:
Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics. SIGKDD Explor. 23(1): 50-58 (2021) - [j11]Thi Ngoc Trang Tran, Alexander Felfernig, Nava Tintarev:
Humanized Recommender Systems: State-of-the-art and Research Issues. ACM Trans. Interact. Intell. Syst. 11(2): 9:1-9:41 (2021) - [j10]Robin Burke, Michael D. Ekstrand, Nava Tintarev, Julita Vassileva:
Preface to the special issue on fair, accountable, and transparent recommender systems. User Model. User Adapt. Interact. 31(3): 371-375 (2021) - [c67]Mats Mulder, Oana Inel, Jasper Oosterman, Nava Tintarev:
Operationalizing Framing to Support Multiperspective Recommendations of Opinion Pieces. FAccT 2021: 478-488 - [c66]Tim Draws, Alisa Rieger, Oana Inel, Ujwal Gadiraju, Nava Tintarev:
A Checklist to Combat Cognitive Biases in Crowdsourcing. HCOMP 2021: 48-59 - [c65]Shabnam Najafian, Tim Draws, Francesco Barile, Marko Tkalcic, Jie Yang, Nava Tintarev:
Exploring User Concerns about Disclosing Location and Emotion Information in Group Recommendations. HT 2021: 155-164 - [c64]Alisa Rieger, Tim Draws, Mariët Theune, Nava Tintarev:
This Item Might Reinforce Your Opinion: Obfuscation and Labeling of Search Results to Mitigate Confirmation Bias. HT 2021: 189-199 - [c63]Tim Draws, Zoltán Szlávik, Benjamin Timmermans, Nava Tintarev, Kush R. Varshney, Michael Hind:
Disparate Impact Diminishes Consumer Trust Even for Advantaged Users. PERSUASIVE 2021: 135-149 - [c62]Francesco Barile, Shabnam Najafian, Tim Draws, Oana Inel, Alisa Rieger, Rishav Hada, Nava Tintarev:
Toward Benchmarking Group Explanations: Evaluating the Effect of Aggregation Strategies versus Explanation. Perspectives@RecSys 2021 - [c61]Tim Draws, Nava Tintarev, Ujwal Gadiraju, Alessandro Bozzon, Benjamin Timmermans:
This Is Not What We Ordered: Exploring Why Biased Search Result Rankings Affect User Attitudes on Debated Topics. SIGIR 2021: 295-305 - [c60]Shabnam Najafian, Amra Delic, Marko Tkalcic, Nava Tintarev:
Factors Influencing Privacy Concern for Explanations of Group Recommendation. UMAP 2021: 14-23 - [c59]Cataldo Musto, Nava Tintarev, Oana Inel, Marco Polignano, Giovanni Semeraro, Jürgen Ziegler:
Workshop on Explainable User Models and Personalized Systems (ExUM 2021). UMAP (Adjunct Publication) 2021: 211-212 - [e10]Judith Masthoff, Eelco Herder, Nava Tintarev, Marko Tkalcic:
Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021, Utrecht, The Netherlands, June, 21-25, 2021. ACM 2021, ISBN 978-1-4503-8366-0 [contents] - [e9]Judith Masthoff, Eelco Herder, Nava Tintarev, Marko Tkalcic:
Adjunct Publication of the 29th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2021, Utrecht, The Netherlands, June 21-25, 2021. ACM 2021, ISBN 978-1-4503-8367-7 [contents] - [i9]Mats Mulder, Oana Inel, Jasper Oosterman, Nava Tintarev:
Operationalizing Framing to Support MultiperspectiveRecommendations of Opinion Pieces. CoRR abs/2101.06141 (2021) - [i8]Tim Draws, Zoltán Szlávik, Benjamin Timmermans, Nava Tintarev, Kush R. Varshney, Michael Hind:
Disparate Impact Diminishes Consumer Trust Even for Advantaged Users. CoRR abs/2101.12715 (2021) - [i7]Alexander Felfernig, Nava Tintarev, Thi Ngoc Trang Tran, Martin Stettinger:
Designing Explanations for Group Recommender Systems. CoRR abs/2102.12413 (2021) - 2020
- [j9]Vladimir Kovalenko, Nava Tintarev, Evgeny Pasynkov, Christian Bird, Alberto Bacchelli:
Does Reviewer Recommendation Help Developers? IEEE Trans. Software Eng. 46(7): 710-731 (2020) - [j8]Yucheng Jin, Nava Tintarev, Nyi Nyi Htun, Katrien Verbert:
Effects of personal characteristics in control-oriented user interfaces for music recommender systems. User Model. User Adapt. Interact. 30(2): 199-249 (2020) - [c58]Federico Maria Cau, Lucio Davide Spano, Nava Tintarev:
Considerations for Applying Logical Reasoning to Explain Neural Network Outputs. XAI.it@AI*IA 2020: 96-103 - [c57]Shabnam Najafian, Daniel Herzog, Sihang Qiu, Oana Inel, Nava Tintarev:
You Do Not Decide for Me! Evaluating Explainable Group Aggregation Strategies for Tourism. HT 2020: 187-196 - [c56]Tim Draws, Jody Liu, Nava Tintarev:
Helping users discover perspectives: Enhancing opinion mining with joint topic models. ICDM (Workshops) 2020: 23-30 - [c55]Shabnam Najafian, Oana Inel, Nava Tintarev:
Someone really wanted that song but it was not me!: Evaluating Which Information to Disclose in Explanations for Group Recommendations. IUI Companion 2020: 85-86 - [c54]Alisa Rieger, Mariët Theune, Nava Tintarev:
Toward Natural Language Mitigation Strategies for Cognitive Biases in Recommender Systems. NL4XAI@INGL 2020: 50-54 - [c53]Mesut Kaya, Derek G. Bridge, Nava Tintarev:
Ensuring Fairness in Group Recommendations by Rank-Sensitive Balancing of Relevance. RecSys 2020: 101-110 - [c52]José Maria Alonso, Senén Barro, Alberto Bugarín, Kees van Deemter, Claire Gardent, Albert Gatt, Ehud Reiter, Carles Sierra, Mariët Theune, Nava Tintarev, Hitoshi Yano, Katarzyna Budzynska:
Interactive Natural Language Technology for Explainable Artificial Intelligence. TAILOR 2020: 63-70 - [c51]Oana Inel, Nava Tintarev, Lora Aroyo:
Eliciting User Preferences for Personalized Explanations for Video Summaries. UMAP 2020: 98-106 - [c50]Cataldo Musto, Nava Tintarev, Oana Inel, Marco Polignano, Giovanni Semeraro, Jürgen Ziegler:
UMAP 2020 Workshop on Explainable User Models and Personalised Systems (ExUM) Chairs' Welcome & Organization. UMAP (Adjunct Publication) 2020: 204-205 - [c49]Cataldo Musto, Nava Tintarev, Oana Inel, Marco Polignano, Giovanni Semeraro, Jürgen Ziegler:
Workshop on Explainable User Models and Personalized Systems (ExUM 2020). UMAP 2020: 406-407 - [e8]Fabio Paternò, Nuria Oliver, Cristina Conati, Lucio Davide Spano, Nava Tintarev:
IUI '20: 25th International Conference on Intelligent User Interfaces, Cagliari, Italy, March 17-20, 2020. ACM 2020, ISBN 978-1-4503-7118-6 [contents] - [i6]Oana Inel, Nava Tintarev, Lora Aroyo:
Eliciting User Preferences for Personalized Explanations for Video Summaries. CoRR abs/2005.00465 (2020) - [i5]Abraham Bernstein, Claes H. de Vreese, Natali Helberger, Wolfgang Schulz, Katharina Anna Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Möller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, Theresa Zueger:
Diversity in News Recommendations. CoRR abs/2005.09495 (2020) - [i4]Boning Gong, Mesut Kaya, Nava Tintarev:
Contextual Personalized Re-Ranking of Music Recommendations through Audio Features. CoRR abs/2009.02782 (2020) - [i3]Tim Draws, Jody Liu, Nava Tintarev:
Helping users discover perspectives: Enhancing opinion mining with joint topic models. CoRR abs/2010.12505 (2020) - [i2]Tim Draws, Nava Tintarev, Ujwal Gadiraju, Alessandro Bozzon, Benjamin Timmermans:
Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics. CoRR abs/2010.14531 (2020)
2010 – 2019
- 2019
- [j7]Kirsten A. Smith, Matt Dennis, Judith Masthoff, Nava Tintarev:
A methodology for creating and validating psychological stories for conveying and measuring psychological traits. User Model. User Adapt. Interact. 29(3): 573-618 (2019) - [c48]Dimitrios Bountouridis, Jaron Harambam, Mykola Makhortykh, Mónica Marrero, Nava Tintarev, Claudia Hauff:
SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments. FAT 2019: 150-159 - [c47]Cataldo Musto, Amon Rapp, Federica Cena, Frank Hopfgartner, Judy Kay, Aonghus Lawlor, Pasquale Lops, Giovanni Semeraro, Nava Tintarev:
UMAP 2019 Workshop on Explainable and Holistic User Modeling (ExHUM) Chairs' Welcome & Organization. UMAP (Adjunct Publication) 2019: 225-227 - [c46]Emily Sullivan, Dimitrios Bountouridis, Jaron Harambam, Shabnam Najafian, Felicia Loecherbach, Mykola Makhortykh, Domokos Kelen, Daricia Wilkinson, David Graus, Nava Tintarev:
Reading News with a Purpose: Explaining User Profiles for Self-Actualization. UMAP (Adjunct Publication) 2019: 241-245 - [c45]Yucheng Jin, Nyi Nyi Htun, Nava Tintarev, Katrien Verbert:
ContextPlay: Evaluating User Control for Context-Aware Music Recommendation. UMAP 2019: 294-302 - 2018
- [j6]Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel:
From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442). Dagstuhl Manifestos 7(1): 96-139 (2018) - [j5]Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, Justin Zobel:
The Dagstuhl Perspectives Workshop on Performance Modeling and Prediction. SIGIR Forum 52(1): 91-101 (2018) - [c44]Adrian Holzer, Nava Tintarev, Samuel Bendahan, Bruno Kocher, Shane Greenup, Denis Gillet:
Digitally Scaffolding Debate in the Classroom. CHI Extended Abstracts 2018 - [c43]Feng Lu, Nava Tintarev:
A Diversity Adjusting Strategy with Personality for Music Recommendation. IntRS@RecSys 2018: 7-14 - [c42]Yucheng Jin, Nava Tintarev, Katrien Verbert:
Effects of personal characteristics on music recommender systems with different levels of controllability. RecSys 2018: 13-21 - [c41]Ishan Ghanmode, Nava Tintarev:
MovieTweeters: An Interactive Interface to Improve Recommendation Novelty. IntRS@RecSys 2018: 24-31 - [c40]Öykü Kapcak, Simone Spagnoli, Vincent Robbemond, Soumitri Vadali, Shabnam Najafian, Nava Tintarev:
TourExplain: A Crowdsourcing Pipeline for Generating Explanations for Groups of Tourists. RecTour@RecSys 2018: 33-36 - [c39]Jayachithra Kumar, Nava Tintarev:
Using Visualizations to Encourage Blind-Spot Exploration. IntRS@RecSys 2018: 53-60 - [c38]Nava Tintarev, Shahin Rostami, Barry Smyth:
Knowing the unknown: visualising consumption blind-spots in recommender systems. SAC 2018: 1396-1399 - [c37]Nava Tintarev, Emily Sullivan, Dror Guldin, Sihang Qiu, Daan Odijk:
Same, Same, but Different: Algorithmic Diversification of Viewpoints in News. UMAP (Adjunct Publication) 2018: 7-13 - [c36]Shabnam Najafian, Nava Tintarev:
Generating Consensus Explanations for Group Recommendations: an exploratory study. UMAP (Adjunct Publication) 2018: 245-250 - [c35]Yucheng Jin, Nava Tintarev, Katrien Verbert:
Effects of Individual Traits on Diversity-Aware Music Recommender User Interfaces. UMAP 2018: 291-299 - 2017
- [c34]Mengmeng Ye, Christoph Lofi, Nava Tintarev:
Memorability of Semantically Grouped Online Reviews. SEMANTiCS (Posters & Demos) 2017 - [c33]Christoph Lofi, Nava Tintarev:
Towards Analogy-based Recommendation: Benchmarking of Perceived Analogy Semantics. ComplexRec@RecSys 2017: 9-13 - [c32]Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Nava Tintarev, Martijn C. Willemsen:
RecSys'17 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems. RecSys 2017: 384-385 - [c31]Nava Tintarev, Christoph Lofi, Cynthia C. S. Liem:
Sequences of Diverse Song Recommendations: An Exploratory Study in a Commercial System. UMAP 2017: 391-392 - [e7]Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Nava Tintarev, Martijn C. Willemsen:
Proceedings of the 4th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2017), Como, Italy, August 27, 2017. CEUR Workshop Proceedings 1884, CEUR-WS.org 2017 [contents] - [i1]Pavel Kucherbaev, Nava Tintarev, Carlos Rodríguez:
Ephemeral Context to Support Robust and Diverse Music Recommendations. CoRR abs/1708.02765 (2017) - 2016
- [j4]Nava Tintarev, Ehud Reiter, Rolf Black, Annalu Waller, Joe Reddington:
Personal storytelling: Using Natural Language Generation for children with complex communication needs, in the wild... Int. J. Hum. Comput. Stud. 92-93: 1-16 (2016) - [j3]Nava Tintarev, John O'Donovan, Alexander Felfernig:
Introduction to the Special Issue on Human Interaction with Artificial Advice Givers. ACM Trans. Interact. Intell. Syst. 6(4): 26:1-26:12 (2016) - [c30]Kirsten A. Smith, Judith Masthoff, Nava Tintarev:
Expressing Emotions as Emoticons for Online Intelligent Agents. BCS HCI 2016 - [c29]Alejandro Ramos-Soto, Nava Tintarev, Rodrigo de Oliveira, Ehud Reiter, Kees van Deemter:
Natural language generation and fuzzy sets: An exploratory study on geographical referring expression generation. FUZZ-IEEE 2016: 587-594 - [c28]Peter Brusilovsky, Alexander Felfernig, Pasquale Lops, John O'Donovan, Giovanni Semeraro, Nava Tintarev, Martijn C. Willemsen:
RecSys'16 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems. RecSys 2016: 413-414 - [c27]Byungkyu Kang, Nava Tintarev, Tobias Höllerer, John O'Donovan:
What am I not Seeing? An Interactive Approach to Social Content Discovery in Microblogs. SocInfo (2) 2016: 279-294 - [e6]Peter Brusilovsky, Alexander Felfernig, Pasquale Lops, John O'Donovan, Giovanni Semeraro, Nava Tintarev, Martijn C. Willemsen:
Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2016), Boston, MA, USA, September 16, 2016. CEUR Workshop Proceedings 1679, CEUR-WS.org 2016 [contents] - 2015
- [c26]Nava Tintarev, Byungkyu Kang, Tobias Höllerer, John O'Donovan:
Inspection Mechanisms for Community-based Content Discovery in Microblogs. IntRS@RecSys 2015: 21-28 - [c25]John O'Donovan, Nava Tintarev, Alexander Felfernig, Peter Brusilovsky, Giovanni Semeraro, Pasquale Lops:
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (#IntRS). RecSys 2015: 347-348 - [c24]Matt Dennis, Kirsten A. Smith, Judith Masthoff, Nava Tintarev:
How Can Skin Check Reminders be Personalised to Patient Conscientiousness? UMAP Workshops 2015 - [c23]Kirsten A. Smith, Judith Masthoff, Nava Tintarev, Wendy Moncur:
Adapting Emotional Support to Personality for Carers Experiencing Stress. UMAP Workshops 2015 - [c22]Nava Tintarev, Matt Green, Judith Masthoff, Frouke Hermens:
Benefits and Risks of Emphasis Adaptation in Study Workflows. UMAP Workshops 2015 - [e5]John O'Donovan, Alexander Felfernig, Nava Tintarev, Peter Brusilovsky, Giovanni Semeraro, Pasquale Lops:
Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, IntRS 2015, co-located with ACM Conference on Recommender Systems (RecSys 2015), Vienna, Austria, September 19, 2015. CEUR Workshop Proceedings 1438, CEUR-WS.org 2015 [contents] - [e4]Alexandra I. Cristea, Judith Masthoff, Alan Said, Nava Tintarev:
Posters, Demos, Late-breaking Results and Workshop Proceedings of the 23rd Conference on User Modeling, Adaptation, and Personalization (UMAP 2015), Dublin, Ireland, June 29 - July 3, 2015. CEUR Workshop Proceedings 1388, CEUR-WS.org 2015 [contents] - [r1]Nava Tintarev, Judith Masthoff:
Explaining Recommendations: Design and Evaluation. Recommender Systems Handbook 2015: 353-382 - 2014
- [j2]Kirsten A. Smith, Judith Masthoff, Nava Tintarev, Wendy Moncur:
The development and evaluation of an emotional support algorithm for carers. Intelligenza Artificiale 8(2): 181-196 (2014) - [c21]Federico Cerutti, Nava Tintarev, Nir Oren:
Formal Arguments, Preferences, and Natural Language Interfaces to Humans: an Empirical Evaluation. ECAI 2014: 207-212 - [c20]Nava Tintarev, Roman Kutlák:
Demo: making plans scrutable with argumentation and natural language generation. IUI Companion 2014: 29-32 - [c19]Nava Tintarev, John O'Donovan, Peter Brusilovsky, Alexander Felfernig, Giovanni Semeraro, Pasquale Lops:
RecSys'14 joint workshop on interfaces and human decision making for recommender systems. RecSys 2014: 383-384 - [c18]Nava Tintarev, Roman Kutlák, Judith Masthoff, Kees van Deemter, Nir Oren, Wamberto Weber Vasconcelos:
Adaptive Visualization of Plans. UMAP Workshops 2014 - [p2]Nava Tintarev, Ehud Reiter, Rolf Black, Annalu Waller:
Natural language generation for augmentative and assistive technologies. Natural Language Generation in Interactive Systems 2014: 252-278 - 2013
- [c17]Sergio Cleger-Tamayo, Juan M. Fernández-Luna, Juan F. Huete, Nava Tintarev:
Being Confident about the Quality of the Predictions in Recommender Systems. ECIR 2013: 411-422 - [c16]Nava Tintarev, Matt Dennis, Judith Masthoff:
Adapting Recommendation Diversity to Openness to Experience: A Study of Human Behaviour. UMAP 2013: 190-202 - 2012
- [j1]Nava Tintarev, Judith Masthoff:
Evaluating the effectiveness of explanations for recommender systems - Methodological issues and empirical studies on the impact of personalization. User Model. User Adapt. Interact. 22(4-5): 399-439 (2012) - [c15]Nava Tintarev, Yolanda Melero, Somayajulu Sripada, Elizabeth Tait, René van der Wal, Chris Mellish:
MinkApp: Generating Spatio-temporal Summaries for Nature Conservation Volunteers. INLG 2012: 17-21 - [c14]Nava Tintarev, Rong Hu, Pearl Pu:
RecSys'12 workshop on interfaces for recommender systems (InterfaceRS'12). RecSys 2012: 355-356 - 2011
- [c13]Rolf Black, Annalu Waller, Nava Tintarev, Ehud Reiter, Joseph Reddington:
A mobile phone based personal narrative system. ASSETS 2011: 171-178 - [c12]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Organizing Committee / Preface. ExaCt 2011 - [c11]Joseph Reddington, Nava Tintarev:
Automatically generating stories from sensor data. IUI 2011: 407-410 - [p1]Nava Tintarev, Judith Masthoff:
Designing and Evaluating Explanations for Recommender Systems. Recommender Systems Handbook 2011: 479-510 - [e3]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Explanation-aware Computing, Papers from the 2011 IJCAI Workshop, Barcelona, Spain, July 16-17, 2011. 2011 [contents] - 2010
- [c10]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake, Daniel Bahls:
Organizing Committee / Preface. ExaCt 2010 - [c9]Nava Tintarev, Ana Flores, Xavier Amatriain:
Off the beaten track: a mobile field study exploring the long tail of tourist recommendations. Mobile HCI 2010: 209-218 - [c8]Rolf Black, Joseph Reddington, Ehud Reiter, Nava Tintarev, Annalu Waller:
Using NLG and Sensors to Support Personal Narrative for Children with Complex Communication Needs. SLPAT@NAACL 2010: 1-9 - [e2]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake, Daniel Bahls:
Explanation-aware Computing, Papers from the 2010 ECAI Workshop, Lisbon, Portugal, August 16, 2010. University of Lisbon, Portugal 2010 [contents]
2000 – 2009
- 2009
- [b1]Nava Tintarev:
Explaining recommendations. University of Aberdeen, UK, 2009 - [c7]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Organizing Committee / Preface. ExaCt 2009 - [c6]Xavier Amatriain, Josep M. Pujol, Nava Tintarev, Nuria Oliver:
Rate it again: increasing recommendation accuracy by user re-rating. RecSys 2009: 173-180 - [e1]Thomas Roth-Berghofer, Nava Tintarev, David B. Leake:
Explanation-aware Computing, Papers from the 2009 IJCAI Workshop, Pasadena, California , USA, July 11-12, 2009. 2009 [contents] - 2008
- [c5]Nava Tintarev, Judith Masthoff:
The Effectiveness of Personalized Movie Explanations: An Experiment Using Commercial Meta-data. AH 2008: 204-213 - 2007
- [c4]Nava Tintarev, Judith Masthoff:
A Survey of Explanations in Recommender Systems. ICDE Workshops 2007: 801-810 - [c3]Nava Tintarev, Judith Masthoff:
Effective explanations of recommendations: user-centered design. RecSys 2007: 153-156 - [c2]Nava Tintarev:
Explanations of recommendations. RecSys 2007: 203-206 - [c1]Nava Tintarev:
Explaining Recommendations. User Modeling 2007: 470-474
Coauthor Index
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