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2020 – today

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2024
[j15]
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Lucia Vadicamo, Rahel Arnold, Werner Bailer, Fabio Carrara, Cathal Gurrin, Nico Hezel, Xinghan Li, Jakub Lokoc, Sebastian Lubos, Zhixin Ma, Nicola Messina, Thao-Nhu Nguyen, Ladislav Peska, Luca Rossetto, Loris Sauter, Klaus Schöffmann, Florian Spiess, Minh-Triet Tran, Stefanos Vrochidis:
Evaluating Performance and Trends in Interactive Video Retrieval: Insights From the 12th VBS Competition. IEEE Access 12: 79342-79366 (2024)
[j14]
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Konstantin Schall, Werner Bailer, Kai Uwe Barthel, Fabio Carrara, Jakub Lokoc, Ladislav Peska, Klaus Schoeffmann, Lucia Vadicamo, Claudio Vairo:
Interactive multimodal video search: an extended post-evaluation for the VBS 2022 competition. Int. J. Multim. Inf. Retr. 13(2): 15 (2024)
[j13]
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  - journals/kais/SkopalPHSB24
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Tomás Skopal, Ladislav Peska, David Hoksza, Ivaná Sixtova, David Bernhauer:
Visualizations for universal deep-feature representations: survey and taxonomy. Knowl. Inf. Syst. 66(2): 811-840 (2024)
[c78]
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Lucas Joos, Bastian Jäckl, Daniel A. Keim, Maximilian T. Fischer, Ladislav Peska, Jakub Lokoc:
Known-Item Search in Video: An Eye Tracking-Based Study. ICMR 2024: 311-319
[c77]
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Patrik Veselý, Ladislav Peska:
RESET: Relational Similarity Extension for V3C1 Video Dataset. MMM (5) 2024: 1-14
[c76]
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  - conf/recsys/SpisakBHP24
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Martin Spisák, Radek Bartyzal, Antonín Hoskovec, Ladislav Peska:
On Interpretability of Linear Autoencoders. RecSys 2024: 975-980
[c75]
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  - conf/sigir/DokoupilPB24
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Patrik Dokoupil, Ladislav Peska, Ludovico Boratto:
SM-RS: Single- and Multi-Objective Recommendations with Contextual Impressions and Beyond-Accuracy Propensity Scores. SIGIR 2024: 988-995
[c74]
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Francesco Barile, Amra Delic, Ladislav Peska, Isabella Saccardi, Federica Lucia Vinella:
GMAP 2024: 3rd Workshop on Group Modeling, Adaptation and Personalization. UMAP (Adjunct Publication) 2024
[c73]
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Patrik Dokoupil, Ludovico Boratto, Ladislav Peska:
User Perceptions of Diversity in Recommender Systems. UMAP 2024: 212-222
[i4]
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  - journals/corr/abs-2406-07264
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Stepán Balcar, Ladislav Peska, Peter Vojtás:
Personalisation of d'Hondt's algorithm and its use in recommender ecosystems. CoRR abs/2406.07264 (2024)
2023
[j12]
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Ly-Duyen Tran, Manh-Duy Nguyen, Duc-Tien Dang-Nguyen, Silvan Heller, Florian Spiess, Jakub Lokoc, Ladislav Peska, Thao-Nhu Nguyen, Omar Shahbaz Khan, Aaron Duane, Björn Þór Jónsson, Luca Rossetto, An-Zi Yen, Ahmed Alateeq, Naushad Alam, Minh-Triet Tran, Graham Healy, Klaus Schoeffmann, Cathal Gurrin:
Comparing Interactive Retrieval Approaches at the Lifelog Search Challenge 2021. IEEE Access 11: 30982-30995 (2023)
[j11]
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Jakub Lokoc, Stelios Andreadis, Werner Bailer, Aaron Duane, Cathal Gurrin, Zhixin Ma, Nicola Messina, Thao-Nhu Nguyen, Ladislav Peska, Luca Rossetto, Loris Sauter, Konstantin Schall, Klaus Schoeffmann, Omar Shahbaz Khan, Florian Spiess, Lucia Vadicamo, Stefanos Vrochidis:
Interactive video retrieval in the age of effective joint embedding deep models: lessons from the 11th VBS. Multim. Syst. 29(6): 3481-3504 (2023)
[j10]
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  - journals/mta/PeskaVVSL23
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Ladislav Peska, Marta Vomlelová, Patrik Veselý, Vít Skrhak, Jakub Lokoc:
Evaluating a Bayesian-like relevance feedback model with text-to-image search initialization. Multim. Tools Appl. 82(15): 22305-22341 (2023)
[c72]
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  - conf/chira/PeskaSHBS23
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Ladislav Peska, Ivaná Sixtova, David Hoksza, David Bernhauer, Tomás Skopal:
Visual Representations for Data Analytics: User Study. CHIRA (2) 2023: 231-243
[c71]
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  - conf/mmm/VeselyP23
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Patrik Veselý, Ladislav Peska:
Less Is More: Similarity Models for Content-Based Video Retrieval. MMM (2) 2023: 54-65
[c70]
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  - conf/mmm/LokocP23
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Jakub Lokoc, Ladislav Peska:
A Study of a Cross-modal Interactive Search Tool Using CLIP and Temporal Fusion. MMM (1) 2023: 397-408
[c69]
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  - conf/mmm/LokocVDP23
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Jakub Lokoc, Zuzana Vopálková, Patrik Dokoupil, Ladislav Peska:
Video Search with CLIP and Interactive Text Query Reformulation. MMM (1) 2023: 628-633
[c68]
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  - conf/recsys/SpisakBHPT23
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Martin Spisák, Radek Bartyzal, Antonín Hoskovec, Ladislav Peska, Miroslav Tuma:
Scalable Approximate NonSymmetric Autoencoder for Collaborative Filtering. RecSys 2023: 763-770
[c67]
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  - conf/recsys/DokoupilPB23
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Patrik Dokoupil, Ladislav Peska, Ludovico Boratto:
Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations. RecSys 2023: 912-918
[c66]
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Patrik Dokoupil, Ladislav Peska:
EasyStudy: Framework for Easy Deployment of User Studies on Recommender Systems. RecSys 2023: 1196-1199
[c65]
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  - conf/recsys/VinagreAPJB23
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João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet:
ORSUM 2023 - 6th Workshop on Online Recommender Systems and User Modeling. RecSys 2023: 1272-1273
[c64]
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Patrik Dokoupil, Ladislav Peska, Ludovico Boratto:
Rows or Columns? Minimizing Presentation Bias When Comparing Multiple Recommender Systems. SIGIR 2023: 2354-2358
[c63]
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  - conf/um/SavcinskyP23
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Richard Savcinsky, Ladislav Peska:
SpotifyExplained: User-centric Mobile Application for Music Exploration. UMAP (Adjunct Publication) 2023: 92-95
[c62]
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  - conf/um/BarileDPSUV23
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Francesco Barile, Amra Delic, Ladislav Peska, Isabella Saccardi, Onuralp Ulusoy, Federica Lucia Vinella:
GMAP 2023: 2nd Workshop on Group Modeling, Adaptation and Personalization. UMAP (Adjunct Publication) 2023: 249-252
[c61]
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Patrik Dokoupil, Ladislav Peska:
The Effect of Similarity Metric and Group Size on Outlier Selection & Satisfaction in Group Recommender Systems. UMAP (Adjunct Publication) 2023: 296-301
[e2]
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João Vinagre, Marie Al-Ghossein, Ladislav Peska, Alípio Mário Jorge, Albert Bifet:
Proceedings of the 6th Workshop on Online Recommender Systems and User Modeling co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023), Singapore, September 19th, 2023. CEUR Workshop Proceedings 3549, CEUR-WS.org 2023 [contents]
[i3]
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  - journals/corr/abs-2307-00654
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Patrik Dokoupil, Ladislav Peska, Ludovico Boratto:
Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations. CoRR abs/2307.00654 (2023)
2022
[j9]
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  - journals/ijmir/HellerGBG0LLMPR22
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Silvan Heller, Viktor Gsteiger, Werner Bailer, Cathal Gurrin, Björn Þór Jónsson, Jakub Lokoc, Andreas Leibetseder, Frantisek Mejzlík, Ladislav Peska, Luca Rossetto, Konstantin Schall, Klaus Schoeffmann, Heiko Schuldt, Florian Spiess, Ly-Duyen Tran, Lucia Vadicamo, Patrik Veselý, Stefanos Vrochidis, Jiaxin Wu:
Interactive video retrieval evaluation at a distance: comparing sixteen interactive video search systems in a remote setting at the 10th Video Browser Showdown. Int. J. Multim. Inf. Retr. 11(1): 1-18 (2022)
[j8]
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  - journals/umuai/BalcarSP22
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Stepán Balcar, Vít Skrhak, Ladislav Peska:
Rank-sensitive proportional aggregations in dynamic recommendation scenarios. User Model. User Adapt. Interact. 32(4): 685-746 (2022)
[c60]
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  - conf/iccai/BalcarPV22
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Stepán Balcar, Ladislav Peska, Peter Vojtás:
Hierarchical Portfolios in Recommender Ecosystems: Multi-level aggregations of heterogeneous ensembles integrating long-term and short-term motivations. ICCAI 2022: 280-285
[c59]
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  - conf/mmm/PeskaL22
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Ladislav Peska, Jakub Lokoc:
Rating-Aware Self-Organizing Maps. MMM (1) 2022: 119-130
[c58]
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  - conf/mmm/LokocBBGHJPRSVV22
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Jakub Lokoc, Werner Bailer, Kai Uwe Barthel, Cathal Gurrin, Silvan Heller, Björn Þór Jónsson, Ladislav Peska, Luca Rossetto, Klaus Schoeffmann, Lucia Vadicamo, Stefanos Vrochidis, Jiaxin Wu:
A Task Category Space for User-Centric Comparative Multimedia Search Evaluations. MMM (1) 2022: 193-204
[c57]
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  - conf/mmm/LokocMSDP22
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Jakub Lokoc, Frantisek Mejzlík, Tomás Soucek, Patrik Dokoupil, Ladislav Peska:
Video Search with Context-Aware Ranker and Relevance Feedback. MMM (2) 2022: 505-510
[c56]
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  - conf/recsys/PeskaB22
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Ladislav Peska, Stepán Balcar:
The Effect of Feedback Granularity on Recommender Systems Performance. RecSys 2022: 586-591
[c55]
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  - conf/recsys/VinagreAJBP22
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João Vinagre, Marie Al-Ghossein, Alípio Mário Jorge, Albert Bifet, Ladislav Peska:
ORSUM 2022 - 5th Workshop on Online Recommender Systems and User Modeling. RecSys 2022: 661-662
[c54]
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Francesco Barile, Amra Delic, Ladislav Peska:
Tutorial on Offline Evaluation for Group Recommender Systems. RecSys 2022: 702-705
[c53]
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  - conf/sigir/PeskaD22
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Ladislav Peska, Patrik Dokoupil:
Towards Results-level Proportionality for Multi-objective Recommender Systems. SIGIR 2022: 1963-1968
[c52]
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  - conf/snams/PeskaVSB22
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Ladislav Peska, Patrik Veselý, Tomás Skopal, Krisztián Búza:
Person Authentication using Visual Representations of Keyboard Typing Dynamics. SNAMS 2022: 1-6
[c51]
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Patrik Dokoupil, Ladislav Peska:
Robustness Against Polarity Bias in Decoupled Group Recommendations Evaluation. UMAP (Adjunct Publication) 2022: 302-307
[e1]
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  - conf/recsys/2022orsum
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João Vinagre, Marie Al-Ghossein, Alípio Mário Jorge, Albert Bifet, Ladislav Peska:
Proceedings of the 5th Workshop on Online Recommender Systems and User Modeling co-located with the 16th ACM Conference on Recommender Systems, ORSUM@RecSys 2022, Seattle, WA, USA, September 23rd, 2022. CEUR Workshop Proceedings 3303, CEUR-WS.org 2022 [contents]
2021
[j7]
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  - journals/ieeemm/RossettoGHPSSSP21
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Luca Rossetto, Ralph Gasser, Silvan Heller, Mahnaz Parian-Scherb, Loris Sauter, Florian Spiess, Heiko Schuldt, Ladislav Peska, Tomás Soucek, Miroslav Kratochvíl, Frantisek Mejzlík, Patrik Veselý, Jakub Lokoc:
On the User-Centric Comparative Remote Evaluation of Interactive Video Search Systems. IEEE Multim. 28(4): 18-28 (2021)
[j6]
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Tomás Grosup, Ladislav Peska, Tomás Skopal:
On augmenting database schemas by latent visual attributes. Knowl. Inf. Syst. 63(9): 2277-2312 (2021)
[c50]
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  - conf/mmm/GajdusekP21
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Pavel Gajdusek, Ladislav Peska:
SpotifyGraph: Visualisation of User's Preferences in Music. MMM (2) 2021: 379-384
[c49]
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  - conf/mmm/PeskaKSSL21
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Ladislav Peska, Gregor Kovalcík, Tomás Soucek, Vít Skrhak, Jakub Lokoc:
W2VV++ BERT Model at VBS 2021. MMM (2) 2021: 467-472
[c48]
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Patrik Dokoupil, Ladislav Peska:
LiGAN: Recommending Artificial Fillers for Police Photo Lineups (Short paper). KaRS/ComplexRec@RecSys 2021
[c47]
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Ladislav Peska, Ladislav Malecek:
Coupled or Decoupled Evaluation for Group Recommendation Methods? Perspectives@RecSys 2021
[c46]
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  - conf/um/MalecekP21
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Ladislav Malecek, Ladislav Peska:
Fairness-preserving Group Recommendations With User Weighting. UMAP (Adjunct Publication) 2021: 4-9
[d1]
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Silvan Heller, Viktor Gsteiger, Werner Bailer, Cathal Gurrin, Björn Þór Jónsson, Jakub Lokoc, Andreas Leibetseder, Frantisek Mejzlík, Ladislav Peska, Luca Rossetto, Konstantin Schall, Klaus Schoeffmann, Heiko Schuldt, Florian Spiess, Ly-Duyen Tran, Lucia Vadicamo, Patrik Veselý, Stefanos Vrochidis, Jiaxin Wu:
Log of the 10th Video Browser Showdown 2021. Zenodo, 2021
2020
[c45]
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  - conf/fuzzIEEE/PeskaV20
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Ladislav Peska, Peter Vojtás:
Predictability of Off-line to On-line Recommender Measures via Scaled Fuzzy Implicators. FUZZ-IEEE 2020: 1-8
[c44]
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Ladislav Peska, Peter Vojtás:
Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerce. HT 2020: 291-300
[c43]
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Josef Starychfojtu, Ladislav Peska:
SmartRecepies: Towards Cooking and Food Shopping Integration via Mobile Recipes Recommender System. iiWAS 2020: 144-148
[c42]
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Stepán Balcar, Ladislav Peska:
Personalized Implicit Negative Feedback Enhancements for Fuzzy D'Hondt's Recommendation Aggregations. iiWAS 2020: 210-215
[c41]
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Ladislav Peska, Frantisek Mejzlík, Tomás Soucek, Jakub Lokoc:
Towards Evaluating and Simulating Keyword Queries for Development of Interactive Known-item Search Systems. ICMR 2020: 281-285
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Michaela Vystrcilová, Ladislav Peska:
Lyrics or Audio for Music Recommendation? WIMS 2020: 190-194

2010 – 2019

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2019
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Ladislav Peska, Tsegaye Misikir Tashu, Tomás Horváth:
Swarm intelligence techniques in recommender systems - A review of recent research. Swarm Evol. Comput. 48: 201-219 (2019)
[c39]
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David Bernhauer, Tomás Skopal, Irena Holubová, Ladislav Peska, Martin Svoboda:
SIMILANT: An Analytic Tool for Similarity Modeling. CIKM 2019: 2889-2892
[c38]
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Ladislav Peska, Hana Trojanová:
LineIT: Similarity Search and Recommendation Tool for Photo Lineup Assembling. DEXA Workshops 2019: 199-209
[c37]
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Irena Holubová, Martin Svoboda, Tomás Skopal, David Bernhauer, Ladislav Peska:
Advanced Behavioral Analyses Using Inferred Social Networks: A Vision. DEXA Workshops 2019: 210-219
[c36]
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Tomás Grosup, Ladislav Peska, Tomás Skopal:
Towards Augmented Database Schemes by Discovery of Latent Visual Attributes. EDBT 2019: 670-673
[c35]
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Ladislav Peska, Stepán Balcar:
Fuzzy D'Hondt's Algorithm for On-line Recommendations Aggregation. ORSUM@RecSys 2019: 2-11
[c34]
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Ladislav Peska, Gregor Kovalcík, Jakub Lokoc:
Towards Automatic Configuration of Interactive Known-Item Search Systems. SISAP 2019: 340-347
[c33]
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Jakub Lokoc, Tomás Soucek, Frantisek Mejzlík, Ladislav Peska:
VIRET tool keyword search at TRECVID 2019 AVS task. TRECVID 2019
[c32]
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  - conf/wims/MalecekBP19
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Ladislav Malecek, Stepán Balcar, Ladislav Peska:
LODBookRec: Linked Open Data for Books Recommendation. WIMS 2019: 12:1-12:6
2018
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Ladislav Peska:
Hybrid recommendations by content-aligned Bayesian personalized ranking. New Rev. Hypermedia Multim. 24(2): 88-109 (2018)
[c31]
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Ladislav Peska, Hana Trojanova:
Personalized Recommendations in Police Photo Lineup Assembling Task. ITAT 2018: 157-160
[c30]
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  - conf/sisap/SkopalPG18
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Tomás Skopal, Ladislav Peska, Tomás Grosup:
Interactive Product Search Based on Global and Local Visual-Semantic Features. SISAP 2018: 87-95
[c29]
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Tomás Skopal, Ladislav Peska, Irena Holubová, Petr Pascenko, Jan Hucín:
Advanced Analytics of Large Connected Data Based on Similarity Modeling. SISAP 2018: 209-216
[c28]
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Ladislav Peska, Hana Trojanova:
Towards Similarity Models in Police Photo Lineup Assembling Tasks. SISAP 2018: 217-225
[i2]
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  - journals/corr/abs-1809-03186
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Ladislav Peska, Peter Vojtás:
Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerce. CoRR abs/1809.03186 (2018)
2017
[j3]
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Ladislav Peska, Krisztián Búza, Júlia Koller:
Drug-target interaction prediction: A Bayesian ranking approach. Comput. Methods Programs Biomed. 152: 15-21 (2017)
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Krisztián Búza, Ladislav Peska:
Drug-target interaction prediction with Bipartite Local Models and hubness-aware regression. Neurocomputing 260: 284-293 (2017)
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Ladislav Peska, Peter Vojtás:
Using Implicit Preference Relations to Improve Recommender Systems. J. Data Semant. 6(1): 15-30 (2017)
[c27]
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Ladislav Peska, Peter Vojtás:
Towards Complex User Feedback and Presentation Context in Recommender Systems. BTW (Workshops) 2017: 203-207
[c26]
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Tomás Skopal, Ladislav Peska, Gregor Kovalcík, Tomás Grosup, Jakub Lokoc:
Product Exploration based on Latent Visual Attributes. CIKM 2017: 2531-2534
[c25]
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Ladislav Peska:
Linking Content Information with Bayesian Personalized Ranking via Multiple Content Alignments. HT 2017: 175-183
[c24]
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Ladislav Peska:
Multimodal Implicit Feedback for Recommender Systems. ITAT 2017: 240-245
[c23]
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Krisztián Búza, Ladislav Peska:
ALADIN: A New Approach for Drug-Target Interaction Prediction. ECML/PKDD (2) 2017: 322-337
[c22]
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Ladislav Peska, Hana Trojanova:
Towards Recommender Systems for Police Photo Lineup. DLRS@RecSys 2017: 19-23
[i1]
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Ladislav Peska, Hana Trojanova:
Towards Recommender Systems for Police Photo Lineup. CoRR abs/1707.01389 (2017)
2016
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Regina Meszlényi, Ladislav Peska, Viktor Gál, Zoltán Vidnyánszky, Krisztián Búza:
A Model for Classification Based on the Functional Connectivity Pattern Dynamics of the Brain. ENIC 2016: 203-208
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Regina Meszlényi, Ladislav Peska, Viktor Gál, Zoltán Vidnyánszky, Krisztián Búza:
Classification of fMRI data using dynamic time warping based functional connectivity analysis. EUSIPCO 2016: 245-249
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Ladislav Peska:
Using the Context of User Feedback in Recommender Systems. MEMICS 2016: 1-12
2015
[c18]
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Ladislav Peska, Peter Vojtás:
Biased k-NN Similarity Content Based Prediction of Movie Tweets Popularity. DATESO 2015: 101-110
[c17]
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Ladislav Peska, Peter Vojtás:
Using Implicit Preference Relations to Improve Content Based Recommending. EC-Web 2015: 3-16
[c16]
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Michal Kopecky, Ladislav Peska, Peter Vojtás, Marta Vomlelová:
Monotonization of User Preferences. FQAS 2015: 29-40
[c15]
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Ladislav Peska, Peter Vojtás:
How to Interpret Implicit User Feedback? RecSys Posters 2015
[c14]
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Ladislav Peska, Peter Vojtás:
Using Linked Open Data in Recommender Systems. WIMS 2015: 17:1-17:6
2014
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Ladislav Peska, Peter Vojtás:
Modelling User Preferences from Implicit Preference Indicators via Compensational Aggregations. EC-Web 2014: 138-145
[c12]
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Ladislav Peska, Peter Vojtás:
Hybrid Recommending Exploiting Multiple DBPedia Language Editions. SemWebEval@ESWC 2014: 144-149
[c11]
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  - conf/icete/VojtasP14
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Peter Vojtás, Ladislav Peska:
e-Shop User Preferences via User Behavior. ICE-B 2014: 68-75
[c10]
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  - conf/ruleml/PeskaV14
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Ladislav Peska, Peter Vojtás:
Interpreting Web Shop User's Behavioral Patterns as Fictitious Explicit Rating for Preference Learning. RuleML 2014: 251-265
[c9]
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  - conf/sofsem/PeskaV14
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Ladislav Peska, Peter Vojtás:
Recommending for Disloyal Customers with Low Consumption Rate. SOFSEM 2014: 455-465
2013
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Ladislav Peska, Peter Vojtás:
Enhancing Recommender System with Linked Open Data. FQAS 2013: 483-494
[c7]
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Ladislav Peska, Peter Vojtás:
Negative implicit feedback in e-commerce recommender systems. WIMS 2013: 45
2012
[c6]
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  - conf/ejc/PeskaLEDVF12
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Ladislav Peska, Ivo Lasek, Alan Eckhardt, Jan Dedek, Peter Vojtás, Dominik Fiser:
Towards web semantization and user understanding. EJC 2012: 63-81
[c5]
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Michal Kopecky, Jaroslav Pokorný, Peter Vojtás, Jirí Kubalík, Kamil Matousek, Milos Maryska, Ota Novotný, Ladislav Peska:
Testing and Evaluating Software in a Social Network Creating Baseline Knowledge. EJC 2012: 127-141
[c4]
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Ladislav Peska, Peter Vojtás:
Evaluating the Importance of Various Implicit Factors in E-commerce. RUE@RecSys 2012: 51-55
[c3]
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Ladislav Peska:
User Feedback and Preferences Mining. UMAP 2012: 382-386
[c2]
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Ladislav Peska, Peter Vojtás:
Estimating importance of implicit factors in e-commerce recommender systems. WIMS 2012: 62:1-62:4
2011
[c1]
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  - conf/iat/PeskaEV11
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Ladislav Peska, Alan Eckhardt, Peter Vojtás:
UPComp - A PHP Component for Recommendation Based on User Behaviour. Web Intelligence/IAT Workshops 2011: 306-309

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