Learning Item Temporal Dynamics for Predicting Buying Sessions. - Veronika Bogina; Tsvi Kuflik; Osnat Mokryn (IUI, 2016)

Building a Bridge between User-Adaptive Systems Evaluation and Software Testing. - Veronika Bogina; Tsvi Kuflik (UMAP (Extended Proceedings), 2016)

The 1st International Workshop on Temporal Reasoning in Recommender Systems. - Mária Bieliková; Veronika Bogina; Tsvi Kuflik; Roy Sasson (RecSys, 2017)

Incorporating Dwell Time in Session-Based Recommendations with Recurrent Neural Networks. - Veronika Bogina; Tsvi Kuflik (RecTemp@RecSys, 2017)

Addressing Temporal Aspects in User Modelling. - Veronika Bogina (UMAP (Adjunct Publication), 2017)

UMAP 2017 THUM Workshop Chairs' Welcome & Organization. - Cataldo Musto; Amon Rapp; Veronika Bogina; Federica Cena; Frank Hopfgartner; Judy Kay; David Konopnicki; Tsvi Kuflik; Bamshad Mobasher; Giovanni Semeraro (UMAP (Adjunct Publication), 2017)

Intelligent user interfaces for algorithmic transparency in emerging technologies. - Styliani Kleanthous; Tsvi Kuflik; Jahna Otterbacher; Alan Hartman; Casey Dugan; Veronika Bogina (IUI Companion, 2019)

"End to End" Towards a Framework for Reducing Biases and Promoting Transparency of Algorithmic Systems. - Avital Shulner-Tal; Khuyagbaatar Batsuren; Veronika Bogina; Fausto Giunchiglia; Alan Hartman; Styliani Kleanthous Loizou; Tsvi Kuflik; Jahna Otterbacher (SMAP, 2019)

FairUMAP 2019 Chairs' Welcome Overview. - Bettina Berendt; Veronika Bogina; Robin Burke; Michael D. Ekstrand; Alan Hartman; Styliani Kleanthous; Tsvi Kuflik; Bamshad Mobasher; Jahna Otterbacher (UMAP (Adjunct Publication), 2019)

A Museum Visitors Classification Based On Behavioral and Demographic Features. - Moayad Mokatren; Veronika Bogina; Alan J. Wecker; Tsvi Kuflik (UMAP (Adjunct Publication), 2019)

Will this session end with a purchase? Inferring current purchase intent of anonymous visitors. - Osnat Mokryn; Veronika Bogina; Tsvi Kuflik (Electron. Commer. Res. Appl., 2019)

Visualizing Program Genres' Temporal-Based Similarity in Linear TV Recommendations. - Veronika Bogina; Julia Sheidin; Tsvi Kuflik; Shlomo Berkovsky (AVI, 2020)

Mitigating Bias in Algorithmic Systems: A Fish-Eye View of Problems and Solutions Across Domains. - Kalia Orphanou; Jahna Otterbacher; Styliani Kleanthous; Khuyagbaatar Batsuren; Fausto Giunchiglia; Veronika Bogina; Avital Shulner-Tal; Alan Hartman; Tsvi Kuflik (CoRR, 2021)

Towards Algorithmic Transparency: A Diversity Perspective. - Fausto Giunchiglia; Jahna Otterbacher; Styliani Kleanthous; Khuyagbaatar Batsuren; Veronika Bogina; Tsvi Kuflik; Avital Shulner-Tal (CoRR, 2021)

Using Wearables Data for Differentiating Between Injured and Non-Injured Athletes. - Maya Reiner; Einat Kodesh; Veronika Bogina; Shany Funk; Tsvi Kuflik (IUI Companion, 2022)

Educating Software and AI Stakeholders About Algorithmic Fairness, Accountability, Transparency and Ethics. - Veronika Bogina; Alan Hartman; Tsvi Kuflik; Avital Shulner-Tal (Int. J. Artif. Intell. Educ., 2022)

Incorporating time-interval sequences in linear TV for next-item prediction. - Veronika Bogina; Yuri Variat; Tsvi Kuflik; Eyal Dim (Expert Syst. Appl., 2022)

Mitigating Bias in Algorithmic Systems - A Fish-eye View. - Kalia Orphanou; Jahna Otterbacher; Styliani Kleanthous; Khuyagbaatar Batsuren; Fausto Giunchiglia; Veronika Bogina; Avital Shulner-Tal; Alan Hartman; Tsvi Kuflik (ACM Comput. Surv., 2023)

Considering temporal aspects in recommender systems: a survey. - Veronika Bogina; Tsvi Kuflik; Dietmar Jannach; Mária Bieliková; Michal Kompan; Christoph Trattner (User Model. User Adapt. Interact., 2023)

A Counterfactual Framework for Learning and Evaluating Explanations for Recommender Systems. - Oren Barkan; Veronika Bogina; Liya Gurevitch; Yuval Asher; Noam Koenigstein (WWW, 2024)

Refining Fidelity Metrics for Explainable Recommendations. - Mikhail Baklanov; Veronika Bogina; Yehonatan Elisha; Yahlly Schein; Liron I. Allerhand; Oren Barkan; Noam Koenigstein (SIGIR, 2025)

Unveiling Creativity in Student Code: A Gaussian Mixture Model Approach. - Veronika Bogina; Arnon Hershkovitz; Noam Koenigstein (UMAP, 2025)

KPAR: Knowledge-aware Path-based Attentive Recommender with Interpretability. - Leigh Eytan; Veronika Bogina; Irad Ben-Gal; Noam Koenigstein (Trans. Recomm. Syst., 2025)