Mgr. Ladislav Peška, Ph.D.

Oblasti zájmu

• Doporučovací systémy
• Uživatelské preference

Výukanahoru

Vedené prácenahoru

Publikační činnostnahoru

2018

Recenzované (časopis, sborník konference) (2)

• Peška L., Trojanová H.: Personalized Recommendations in Police Photo Lineup Assembling Task, in ITAT 2018: Information Technologies – Applications and Theory Proceedings of the 18th conference ITAT 2018 Plejsy, Slovakia, September 21–25, 2018, Plejsy, CEUR Workshop Proceedings, ISSN: 1613-0073, pp. 157-160, 2018 - text
• Peška L., Trojanová H.: Towards Similarity Models in Police Photo Lineup Assembling Tasks, in Similarity Search and Applications, Lima, Springer International Publishing, ISBN: 978-3-030-02223-5, 2018

2017

Recenzované (časopis, sborník konference) (9)

• Buza K., Peška L.: ALADIN: A New Approach for Drug--Target Interaction Prediction, in Machine Learning and Knowledge Discovery in Databases, SKOPJE, MACEDONIA, Springer International Publishing, ISBN: 978-3-319-71246-8, pp. 322-337, 2017 - text
• Buza K., Peška L.: Drug-target interaction prediction with Bipartite Local Models and hubness-aware regression, in Neurocomputing, Vol. 260, Num. 10, ISSN: 0925-2312, pp. 284-293, 2017 - text
• Peška L.: Linking Content Information with Bayesian Personalized Ranking via Multiple Content Alignments, in Proceedings of the 28th ACM Conference on Hypertext and Social Media, Prague, Czech Republic, ACM, ISBN: 978-1-4503-4708-2, pp. 175-183, 2017 - text
• Peška L.: Multimodal Implicit Feedback for Recommender Systems, in Proceedings of the 17th Conference on Information Technologies - Applications and Theory (ITAT 2017), Martinske Hole, CEUR-WS, ISSN: 1613-0073, pp. 240-245, 2017 - text
• Peška L., Krisztian B., Julia K.: Drug-target interaction prediction: A Bayesian ranking approach, in Computer Methods and Programs in Biomedicine, Vol. 152, Num. 12, ISSN: 0169-2607, pp. 15-21, 2017 - text
• Peška L., Trojanová H.: Towards Recommender Systems for Police Photo Lineup, in Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, Como, Italy, Association for Computing Machinery, ISBN: 978-1-4503-5353-3, pp. 19-23, 2017 - text
• Peška L., Vojtáš P.: Towards Complex User Feedback and Presentation Context in Recommender Systems, in Datenbanksysteme für Business, Technologie und Web (BTW 2017), 17. Fachtagung des GI-Fachbereichs „Datenbanken und Informationssysteme" (DBIS), 6.-10. März 2017, Stuttgart, Germany, Workshopband, Stuttgart, Germany, Gesellschaft für Informatik e.V., ISBN: 978-3-88579-660-2, pp. 127-134, 2017 - text
• Peška L., Vojtáš P.: Using Implicit Preference Relations to Improve Recommender Systems, in Journal on Data Semantics, Vol. 6, Num. 1, ISSN: 1861-2032, pp. 15-30, 2017 - text
• Skopal T., Peška L., Kovalčík G., Grošup T., Lokoč J.: Product exploration based on latent visual attributes, in Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, Singapore, ACM, ISBN: 978-1-4503-4918-5, pp. 2531-2534, 2017

2016

Recenzované (časopis, sborník konference) (3)

• Meszlényi R., Peška L., Gál V., Vidnyánszky Z., Buza K.: A model for classification based on the functional connectivity pattern dynamics of the brain, in 2016 Third European Network Intelligence Conference (ENIC), Wrocław, Poland, IEEE, ISBN: 978-1-5090-3455-0, pp. 203-208, 2016 - text
• Meszlényi R., Peška L., Gál V., Vidnyánszky Z., Buza K.: Classification of fMRI data using Dynamic Time Warping based functional connectivity analysis, in 24th European Signal Processing Conference, EUSIPCO 2016, Budapest, Hungary, IEEE, ISBN: 978-0-9928626-5-7, ISSN: 2219-5491, pp. 245-249, 2016 - text
• Peška L.: Using the Context of User Feedback in Recommender Systems, in ELECTRONIC PROCEEDINGS IN THEORETICAL COMPUTER SCIENCE, Telč, Česká Republika, Open Publishing Association, ISSN: 2075-2180, pp. 1-12, 2016 - text

2015

Recenzované (časopis, sborník konference) (5)

• Kopecký M., Peška L., Vojtáš P., Vomlelová M.: Monotonization of User Preferences, in Proceedings of the 11th International Conference FQAS 2015, Krakov, Springer, ISBN: 978-3-319-26154-6, ISSN: 2194-5357, pp. 29-40, 2015
• Peška L., Vojtáš P.: Biased k-NN Similarity Content Based Prediction of Movie Tweets Popularity, in Proceedings of the Dateso 2015 Annual International Workshop on DAtabases, TExts, Specifications and Objects, Neprivec u Sobotky, Jicin, Czech Republic, CEUR-WS.org, ISSN: 1613-0073, pp. 101-110, 2015 - text
• Peška L., Vojtáš P.: How to Interpret Implicit User Feedback?, in RecSys 2015 Poster Proceeding, Vienna, Austria, CEUR-WS.org, ISSN: 1613-0073, pp. nestránkováno, 2015 - text
• Peška L., Vojtáš P.: Using Implicit Preference Relations to Improve Content Based Recommending, in E-Commerce and Web Technologies, 16th International Conference on Electronic Commerce and Web Technologies, EC-Web 2015, Valencia, Spain, September 2015, Revised Selected Papers, Valencia, Spain, Springer, ISBN: 978-3-319-27728-8, ISSN: 1865-1348, pp. 3-16, 2015 - text
• Peška L., Vojtáš P.: Using Linked Open Data in Recommender Systems, in Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics, Limassol, Cyprus, ACM, ISBN: 978-1-4503-3293-4, pp. 17_1-17_6, 2015 - text

2014

Recenzované (časopis, sborník konference) (6)

• Peška L.: IPIget: The Component for Collecting Implicit User Preference Indicators, in Proceedings of the 14th conference Information Technologies - Applications and Theory (ITAT 2014) - Workshops and Posters, Demänovská Dolina, Slovakia, Ústav informatiky AV ČR, ISBN: 978-80-87136-19-5, pp. 22-26, 2014
• Peška L., Vojtáš P.: Hybrid Recommending Exploiting Multiple DBPedia Language Editions, in Semantic Web Evaluation Challenge, Anissaras, Crete, Greece, Springer Verlag, ISBN: 978-3-319-12023-2, ISSN: 1865-0929, pp. 144-149, 2014
• Peška L., Vojtáš P.: Interpreting Web Shop User's Behavioral Patterns as Fictitious Explicit Rating for Preference Learning, in Rules on the Web. From Theory to Applications, Prague, Czech Republic, Springer, ISBN: 978-3-319-09869-2, ISSN: 0302-9743, pp. 251-265, 2014
• Peška L., Vojtáš P.: Modelling User Preferences from Implicit Preference Indicators via Compensational Aggregations, in E-Commerce and Web Technologies, Munich, Germany, Springer, ISBN: 978-3-319-10490-4, ISSN: 1865-1348, pp. 138-145, 2014
• Peška L., Vojtáš P.: Recommending for Disloyal Customers with Low Consumption Rate, in SOFSEM 2014: Theory and Practice of Computer Science, Nový Smokovec, Slovakia, Springer, ISBN: 978-3-319-04297-8, ISSN: 0302-9743, pp. 455-465, 2014
• Vojtáš P., Peška L.: e-Shop User Preferences via User Behavior, in ICE-B 2014 - Proceedings of the 11th International Conference on e-Business, Vienna, Austria, 28-30 August, 2014, Vienna, Austria, SciTePress, ISBN: 978-989-758-043-7, pp. 68-75, 2014

2013

Recenzované (časopis, sborník konference) (7)

• Kopecký M., Pokorný J., Vojtáš P., Kubalík J., Matoušek K., Maryška M., Novotný O., Peška L.: Testing and Evaluating Software in a Social Network Creating Baseline Knowledge, in Frontiers in Artificial Intelligence and Applications, Vol. neuveden, Num. 251, ISSN: 0922-6389, pp. 127-141, 2013
• Peška L.: How Far Ahead Can Recommender Systems Predict?, in ITAT 2013: Information Technologies—Applications and Theory (Proceedings), Donovaly, Slovakia, CreateSpace Independent Publishing Platform, ISBN: 978-1-4909-5208-6, pp. 22-26, 2013
• Peška L., Lašek I., Eckhardt A., Dědek J., Vojtáš P., Dominik F.: Towards web semantization and user understanding, in Frontiers in Artificial Intelligence and Applications, Vol. 251, Num. January, ISSN: 0922-6389, pp. 63-81, 2013
• Peška L., Vojtáš P.: Enhancing Recommender System with Linked Open Data, in Lecture Notes in Computer Science, Granada, Spain, Springer Berlin / Heidelberg, ISBN: 978-3-642-40768-0, ISSN: 0302-9743, pp. 483-494, 2013
• Peška L., Vojtáš P.: Estimating importance of implicit factors in E-commerce recommender systems, in Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics, Craiova, Romania, ACM, ISBN: 978-1-4503-0915-8, pp. 1-4, 2013
• Peška L., Vojtáš P.: Evaluating various implicit factors in e-commerce, accepted for publication in CEUR Workshop Proceedings, Dublin, Ireland, Ceur-WS.org, ISSN: 1613-0073, pp. 51-55, 2013
• Peška L., Vojtáš P.: Negative implicit feedback in e-commerce recommender systems, in Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics, Madrid, Spain, ACM, ISBN: 1-4503-1850-9, pp. 451-454, 2013

Kapitoly v knihách (1)

• Nečaský M., Fišer D., Lašek I., Peška L., Vojtáš P.: User Assisted Creation of Open-Linked Data for Training Web Information Extraction in a Social Network, in Cases On Open-Linked Data and Semantic Web Applications, IGI Global, ISBN: 978-1-4666-2827-4, pp. 28-38, 2013

2012

Recenzované (časopis, sborník konference) (1)

• Peška L.: User Feedback and Preferences Mining, in Lecture Notes in Computer Science, Vol. neuveden, Num. 7379, ISSN: 0302-9743, pp. 382-386, 2012

2011

Recenzované (časopis, sborník konference) (1)

• Peška L., Eckhardt A., Vojtáš P.: UPComp - A PHP Component for Recommendation Based on User Behaviour, in Proceedings of WI-IAT 2011, Lyon, France, IEEE Computer Society, ISBN: 978-1-4577-1373-6, pp. 306-309, 2011

Kontaktynahoru

• peska<at>ksi.mff.cuni.cz
• http://www.ksi.mff.cuni.cz/~peska/
• místnost 208, 2. patro