UPComp - A PHP Component for Recommendation Based on User Behaviour. - Ladislav Peska; Alan Eckhardt; Peter Vojtás (Web Intelligence/IAT Workshops, 2011)

Testing and Evaluating Software in a Social Network Creating Baseline Knowledge. - Michal Kopecky; Jaroslav Pokorný; Peter Vojtás; Jirí Kubalík; Kamil Matousek; Milos Maryska; Ota Novotný; Ladislav Peska (EJC, 2012)

Towards web semantization and user understanding. - Ladislav Peska; Ivo Lasek; Alan Eckhardt; Jan Dedek; Peter Vojtás; Dominik Fiser (EJC, 2012)

Evaluating the Importance of Various Implicit Factors in E-commerce. - Ladislav Peska; Peter Vojtás (RUE@RecSys, 2012)

User Feedback and Preferences Mining. - Ladislav Peska (UMAP, 2012)

Estimating importance of implicit factors in e-commerce recommender systems. - Ladislav Peska; Peter Vojtás (WIMS, 2012)

Enhancing Recommender System with Linked Open Data. - Ladislav Peska; Peter Vojtás (FQAS, 2013)

Negative implicit feedback in e-commerce recommender systems. - Ladislav Peska; Peter Vojtás (WIMS, 2013)

Modelling User Preferences from Implicit Preference Indicators via Compensational Aggregations. - Ladislav Peska; Peter Vojtás (EC-Web, 2014)

Hybrid Recommending Exploiting Multiple DBPedia Language Editions. - Ladislav Peska; Peter Vojtás (SemWebEval@ESWC, 2014)

e-Shop User Preferences via User Behavior. - Peter Vojtás; Ladislav Peska (ICE-B, 2014)

Interpreting Web Shop User's Behavioral Patterns as Fictitious Explicit Rating for Preference Learning. - Ladislav Peska; Peter Vojtás (RuleML, 2014)

Recommending for Disloyal Customers with Low Consumption Rate. - Ladislav Peska; Peter Vojtás (SOFSEM, 2014)

Biased k-NN Similarity Content Based Prediction of Movie Tweets Popularity. - Ladislav Peska; Peter Vojtás (DATESO, 2015)

Using Implicit Preference Relations to Improve Content Based Recommending. - Ladislav Peska; Peter Vojtás (EC-Web, 2015)

Monotonization of User Preferences. - Michal Kopecky; Ladislav Peska; Peter Vojtás; Marta Vomlelová (FQAS, 2015)

How to Interpret Implicit User Feedback? - Ladislav Peska; Peter Vojtás (RecSys Posters, 2015)

Using Linked Open Data in Recommender Systems. - Ladislav Peska; Peter Vojtás (WIMS, 2015)

A Model for Classification Based on the Functional Connectivity Pattern Dynamics of the Brain. - Regina Meszlényi; Ladislav Peska; Viktor Gál; Zoltán Vidnyánszky; Krisztián Búza (ENIC, 2016)

Classification of fMRI data using dynamic time warping based functional connectivity analysis. - Regina Meszlényi; Ladislav Peska; Viktor Gál; Zoltán Vidnyánszky; Krisztián Búza (EUSIPCO, 2016)

Using the Context of User Feedback in Recommender Systems. - Ladislav Peska (MEMICS, 2016)

Towards Complex User Feedback and Presentation Context in Recommender Systems. - Ladislav Peska; Peter Vojtás (BTW (Workshops), 2017)

Product Exploration based on Latent Visual Attributes. - Tomás Skopal; Ladislav Peska; Gregor Kovalcík; Tomás Grosup; Jakub Lokoc (CIKM, 2017)

Linking Content Information with Bayesian Personalized Ranking via Multiple Content Alignments. - Ladislav Peska (HT, 2017)

Multimodal Implicit Feedback for Recommender Systems. - Ladislav Peska (ITAT, 2017)

ALADIN: A New Approach for Drug-Target Interaction Prediction. - Krisztián Búza; Ladislav Peska (ECML/PKDD (2), 2017)

Towards Recommender Systems for Police Photo Lineup. - Ladislav Peska; Hana Trojanova (DLRS@RecSys, 2017)

Drug-target interaction prediction: A Bayesian ranking approach. - Ladislav Peska; Krisztián Búza; Júlia Koller (Comput. Methods Programs Biomed., 2017)

Drug-target interaction prediction with Bipartite Local Models and hubness-aware regression. - Krisztián Búza; Ladislav Peska (Neurocomputing, 2017)

Using Implicit Preference Relations to Improve Recommender Systems. - Ladislav Peska; Peter Vojtás (J. Data Semant., 2017)

Personalized Recommendations in Police Photo Lineup Assembling Task. - Ladislav Peska; Hana Trojanova (ITAT, 2018)

Towards Similarity Models in Police Photo Lineup Assembling Tasks. - Ladislav Peska; Hana Trojanova (SISAP, 2018)

Interactive Product Search Based on Global and Local Visual-Semantic Features. - Tomás Skopal; Ladislav Peska; Tomás Grosup (SISAP, 2018)

Advanced Analytics of Large Connected Data Based on Similarity Modeling. - Tomás Skopal; Ladislav Peska; Irena Holubová; Petr Pascenko; Jan Hucín (SISAP, 2018)

Hybrid recommendations by content-aligned Bayesian personalized ranking. - Ladislav Peska (New Rev. Hypermedia Multim., 2018)

SIMILANT: An Analytic Tool for Similarity Modeling. - David Bernhauer; Tomás Skopal; Irena Holubová; Ladislav Peska; Martin Svoboda (CIKM, 2019)

Advanced Behavioral Analyses Using Inferred Social Networks: A Vision. - Irena Holubová; Martin Svoboda; Tomás Skopal; David Bernhauer; Ladislav Peska (DEXA Workshops, 2019)

LineIT: Similarity Search and Recommendation Tool for Photo Lineup Assembling. - Ladislav Peska; Hana Trojanová (DEXA Workshops, 2019)

Towards Augmented Database Schemes by Discovery of Latent Visual Attributes. - Tomás Grosup; Ladislav Peska; Tomás Skopal (EDBT, 2019)

Fuzzy D'Hondt's Algorithm for On-line Recommendations Aggregation. - Ladislav Peska; Stepán Balcar (ORSUM@RecSys, 2019)

Towards Automatic Configuration of Interactive Known-Item Search Systems. - Ladislav Peska; Gregor Kovalcík; Jakub Lokoc (SISAP, 2019)

VIRET tool keyword search at TRECVID 2019 AVS task. - Jakub Lokoc; Tomás Soucek; Frantisek Mejzlík; Ladislav Peska (TRECVID, 2019)

LODBookRec: Linked Open Data for Books Recommendation. - Ladislav Malecek; Stepán Balcar; Ladislav Peska (WIMS, 2019)

Swarm intelligence techniques in recommender systems - A review of recent research. - Ladislav Peska; Tsegaye Misikir Tashu; Tomás Horváth (Swarm Evol. Comput., 2019)

Predictability of Off-line to On-line Recommender Measures via Scaled Fuzzy Implicators. - Ladislav Peska; Peter Vojtás (FUZZ-IEEE, 2020)

Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerce. - Ladislav Peska; Peter Vojtás (HT, 2020)

Personalized Implicit Negative Feedback Enhancements for Fuzzy D'Hondt's Recommendation Aggregations. - Stepán Balcar; Ladislav Peska (iiWAS, 2020)

SmartRecepies: Towards Cooking and Food Shopping Integration via Mobile Recipes Recommender System. - Josef Starychfojtu; Ladislav Peska (iiWAS, 2020)

Towards Evaluating and Simulating Keyword Queries for Development of Interactive Known-item Search Systems. - Ladislav Peska; Frantisek Mejzlík; Tomás Soucek; Jakub Lokoc (ICMR, 2020)

Lyrics or Audio for Music Recommendation? - Michaela Vystrcilová; Ladislav Peska (WIMS, 2020)

SpotifyGraph: Visualisation of User's Preferences in Music. - Pavel Gajdusek; Ladislav Peska (MMM (2), 2021)

W2VV++ BERT Model at VBS 2021. - Ladislav Peska; Gregor Kovalcík; Tomás Soucek; Vít Skrhak; Jakub Lokoc (MMM (2), 2021)

LiGAN: Recommending Artificial Fillers for Police Photo Lineups (Short paper). - Patrik Dokoupil; Ladislav Peska (KaRS/ComplexRec@RecSys, 2021)

Coupled or Decoupled Evaluation for Group Recommendation Methods? - Ladislav Peska; Ladislav Malecek (Perspectives@RecSys, 2021)

Fairness-preserving Group Recommendations With User Weighting. - Ladislav Malecek; Ladislav Peska (UMAP (Adjunct Publication), 2021)

On the User-Centric Comparative Remote Evaluation of Interactive Video Search Systems. - Luca Rossetto; Ralph Gasser; Silvan Heller; Mahnaz Parian-Scherb; Loris Sauter; Florian Spiess 001; Heiko Schuldt; Ladislav Peska; Tomás Soucek; Miroslav Kratochvíl; Frantisek Mejzlík; Patrik Veselý; et al. (IEEE Multim., 2021)

On augmenting database schemas by latent visual attributes. - Tomás Grosup; Ladislav Peska; Tomás Skopal (Knowl. Inf. Syst., 2021)

Log of the 10th Video Browser Showdown 2021. - Silvan Heller; Viktor Gsteiger; Werner Bailer; Cathal Gurrin; Björn Þór Jónsson 001; Jakub Lokoc; Andreas Leibetseder; Frantisek Mejzlík; Ladislav Peska; Luca Rossetto; Konstantin Schall; Klaus Schoeffmann; et al. (Zenodo, 2021)

Hierarchical Portfolios in Recommender Ecosystems: Multi-level aggregations of heterogeneous ensembles integrating long-term and short-term motivations. - Stepán Balcar; Ladislav Peska; Peter Vojtás (ICCAI, 2022)

A Task Category Space for User-Centric Comparative Multimedia Search Evaluations. - Jakub Lokoc; Werner Bailer; Kai Uwe Barthel; Cathal Gurrin; Silvan Heller; Björn Þór Jónsson 001; Ladislav Peska; Luca Rossetto; Klaus Schoeffmann; Lucia Vadicamo; Stefanos Vrochidis; Jiaxin Wu 001 (MMM (1), 2022)

Video Search with Context-Aware Ranker and Relevance Feedback. - Jakub Lokoc; Frantisek Mejzlík; Tomás Soucek; Patrik Dokoupil; Ladislav Peska (MMM (2), 2022)

Rating-Aware Self-Organizing Maps. - Ladislav Peska; Jakub Lokoc (MMM (1), 2022)

Tutorial on Offline Evaluation for Group Recommender Systems. - Francesco Barile; Amra Delic; Ladislav Peska (RecSys, 2022)

The Effect of Feedback Granularity on Recommender Systems Performance. - Ladislav Peska; Stepán Balcar (RecSys, 2022)

ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling. - João Vinagre; Marie Al-Ghossein; Alípio Mário Jorge; Albert Bifet; Ladislav Peska (RecSys, 2022)

Towards Results-level Proportionality for Multi-objective Recommender Systems. - Ladislav Peska; Patrik Dokoupil (SIGIR, 2022)

Person Authentication using Visual Representations of Keyboard Typing Dynamics. - Ladislav Peska; Patrik Veselý; Tomás Skopal; Krisztián Búza (SNAMS, 2022)

Robustness Against Polarity Bias in Decoupled Group Recommendations Evaluation. - Patrik Dokoupil; Ladislav Peska (UMAP (Adjunct Publication), 2022)

Interactive video retrieval evaluation at a distance: comparing sixteen interactive video search systems in a remote setting at the 10th Video Browser Showdown. - Silvan Heller; Viktor Gsteiger; Werner Bailer; Cathal Gurrin; Björn Þór Jónsson 001; Jakub Lokoc; Andreas Leibetseder; Frantisek Mejzlík; Ladislav Peska; Luca Rossetto; Konstantin Schall; Klaus Schoeffmann; et al. (Int. J. Multim. Inf. Retr., 2022)

Rank-sensitive proportional aggregations in dynamic recommendation scenarios. - Stepán Balcar; Vít Skrhak; Ladislav Peska (User Model. User Adapt. Interact., 2022)

Visual Representations for Data Analytics: User Study. - Ladislav Peska; Ivaná Sixtova; David Hoksza; David Bernhauer; Tomás Skopal (CHIRA (2), 2023)

A Study of a Cross-modal Interactive Search Tool Using CLIP and Temporal Fusion. - Jakub Lokoc; Ladislav Peska (MMM (1), 2023)

Video Search with CLIP and Interactive Text Query Reformulation. - Jakub Lokoc; Zuzana Vopálková; Patrik Dokoupil; Ladislav Peska (MMM (1), 2023)

Less Is More: Similarity Models for Content-Based Video Retrieval. - Patrik Veselý; Ladislav Peska (MMM (2), 2023)

EasyStudy: Framework for Easy Deployment of User Studies on Recommender Systems. - Patrik Dokoupil; Ladislav Peska (RecSys, 2023)

Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations. - Patrik Dokoupil; Ladislav Peska; Ludovico Boratto (RecSys, 2023)

Scalable Approximate NonSymmetric Autoencoder for Collaborative Filtering. - Martin Spisák; Radek Bartyzal; Antonín Hoskovec; Ladislav Peska; Miroslav Tuma (RecSys, 2023)

ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling. - João Vinagre; Marie Al-Ghossein; Ladislav Peska; Alípio Mário Jorge; Albert Bifet (RecSys, 2023)

Rows or Columns? Minimizing Presentation Bias When Comparing Multiple Recommender Systems. - Patrik Dokoupil; Ladislav Peska; Ludovico Boratto (SIGIR, 2023)

GMAP 2023: 2nd Workshop on Group Modeling, Adaptation and Personalization. - Francesco Barile; Amra Delic; Ladislav Peska; Isabella Saccardi; Onuralp Ulusoy; Federica Lucia Vinella (UMAP (Adjunct Publication), 2023)

The Effect of Similarity Metric and Group Size on Outlier Selection & Satisfaction in Group Recommender Systems. - Patrik Dokoupil; Ladislav Peska (UMAP (Adjunct Publication), 2023)

SpotifyExplained: User-centric Mobile Application for Music Exploration. - Richard Savcinsky; Ladislav Peska (UMAP (Adjunct Publication), 2023)

Comparing Interactive Retrieval Approaches at the Lifelog Search Challenge 2021. - Ly-Duyen Tran; Manh-Duy Nguyen; Duc-Tien Dang-Nguyen; Silvan Heller; Florian Spiess 001; Jakub Lokoc; Ladislav Peska; Thao-Nhu Nguyen; Omar Shahbaz Khan; Aaron Duane; Björn Þór Jónsson 001; Luca Rossetto; et al. (IEEE Access, 2023)

Evaluating a Bayesian-like relevance feedback model with text-to-image search initialization. - Ladislav Peska; Marta Vomlelová; Patrik Veselý; Vít Skrhak; Jakub Lokoc (Multim. Tools Appl., 2023)

Interactive video retrieval in the age of effective joint embedding deep models: lessons from the 11th VBS. - Jakub Lokoc; Stelios Andreadis; Werner Bailer; Aaron Duane; Cathal Gurrin; Zhixin Ma 001; Nicola Messina; Thao-Nhu Nguyen; Ladislav Peska; Luca Rossetto; Loris Sauter; Konstantin Schall; et al. (Multim. Syst., 2023)

Comparing User Interfaces for Customizing Multi-Objective Recommender Systems. - Patrik Dokoupil; Ludovico Boratto; Ladislav Peska (IntRS@RecSys, 2024)

Known-Item Search in Video: An Eye Tracking-Based Study. - Lucas Joos; Bastian Jäckl; Daniel A. Keim; Maximilian T. Fischer; Ladislav Peska; Jakub Lokoc (ICMR, 2024)

RESET: Relational Similarity Extension for V3C1 Video Dataset. - Patrik Veselý; Ladislav Peska (MMM (5), 2024)

On Interpretability of Linear Autoencoders. - Martin Spisák; Radek Bartyzal; Antonín Hoskovec; Ladislav Peska (RecSys, 2024)

SM-RS: Single- and Multi-Objective Recommendations with Contextual Impressions and Beyond-Accuracy Propensity Scores. - Patrik Dokoupil; Ladislav Peska; Ludovico Boratto (SIGIR, 2024)

GMAP 2024: 3rd Workshop on Group Modeling, Adaptation and Personalization. - Francesco Barile; Amra Delic; Ladislav Peska; Isabella Saccardi; Federica Lucia Vinella (UMAP (Adjunct Publication), 2024)

User Perceptions of Diversity in Recommender Systems. - Patrik Dokoupil; Ludovico Boratto; Ladislav Peska (UMAP, 2024)

Evaluating Performance and Trends in Interactive Video Retrieval: Insights From the 12th VBS Competition. - Lucia Vadicamo; Rahel Arnold; Werner Bailer; Fabio Carrara; Cathal Gurrin; Nico Hezel; Xinghan Li; Jakub Lokoc; Sebastian Lubos; Zhixin Ma 001; Nicola Messina; Thao-Nhu Nguyen; et al. (IEEE Access, 2024)

Personalisation of d'Hondt's algorithm and its use in recommender ecosystems. - Stepán Balcar; Ladislav Peska; Peter Vojtás (CoRR, 2024)

Visualizations for universal deep-feature representations: survey and taxonomy. - Tomás Skopal; Ladislav Peska; David Hoksza; Ivaná Sixtova; David Bernhauer (Knowl. Inf. Syst., 2024)

Interactive multimodal video search: an extended post-evaluation for the VBS 2022 competition. - Konstantin Schall; Werner Bailer; Kai Uwe Barthel; Fabio Carrara; Jakub Lokoc; Ladislav Peska; Klaus Schoeffmann; Lucia Vadicamo; Claudio Vairo (Int. J. Multim. Inf. Retr., 2024)

GMAP 2025: 4th Workshop on Group Modeling, Adaptation and Personalization. - Francesco Barile; Amra Delic; Ladislav Peska; Isabella Saccardi; Cedric Waterschoot (UMAP (Adjunct Publication), 2025)

Effects of Quantitative Explanations on Fairness Perception in Group Recommender Systems. - Patrik Dokoupil; Ladislav Peska (UMAP, 2025)

Bridging the Rift: A Critical Perspective on the Divergence in Group Recommender Systems Research. - Ladislav Peska; Amra Delic; Francesco Barile; Patrik Dokoupil (UMAP (Adjunct Publication), 2025)

It's Time to Let Go: Stopping Criteria Recommendations in Content-rich Domains. - Matej Scerba; Ladislav Peska (UMAP (Adjunct Publication), 2025)

Unified Visual-Aware Representations for Data Analytics. - Ladislav Peska; Ivaná Sixtova; David Hoksza; David Bernhauer; Jakub Lokoc; Tomás Skopal (IEEE Access, 2025)

Accuracy and beyond-accuracy perspectives of controllable multi-objective recommender systems. - Patrik Dokoupil; Ludovico Boratto; Ladislav Peska (Inf. Process. Manag., 2025)