Researchers cover topics of new trends in design, development and usage of adaptive social web-based systems including analysis of user logs and user’s behaviour prediction. We explore novel recommenders design and application. Hand by hand with the user generated content increase, we explore the sentiment analysis and various methods for discriminative keyword extraction with focus on neural networks. We research novel methods for information extraction by incorporating natural language processing. The User eXperience (UX) is one of the essential sources of information about user’s behavior, thus studies examining the user’s behaviour and experience provided in the User eXperience and Interaction research center support our research outputs.
Recommender Systems, User Modelling and Personalization, User Experience and Interaction, Human Computing, Information Retrieval and Exploratory Search, Natural Language Processing
|Aims her research to human interactions on the Web with special emphasis on user modelling and personalization, context awareness, collaborations and usability. This includes research of methods for automated analysis and modelling user feedback, and its evaluation by (multi/group) user studies employing eye trackers.
Covers by her research interests the area of information systems, quality of information systems, security and privacy, user modelling, in particular she focuses on similarity of texts and behavioral biometric authentication.
|Aims his research at problems in the recommender systems and users’ behavior prediction. Dr. Michal Barla covers by his research interests an area of clickstream data analysis for user modeling with a special focus on unsupervised methods, including neural networks.
Dedicates his research to user modelling, user experience and web personalization. In particular, he focuses on user characteristics acquisition based on (semi)automatic analysis of user's feedback, research of methods for automatic identification of usability problems, designing qualitative/quantitative usability studies, online/remote usability testing, and designing user interfaces.
|His particularly interested in applying intelligent approaches and creating online learning experiences for students mainly via active problem solving and collaborative approaches. Additionally, he is using eye tracking for research in program comprehension.
dedicates his research to the intersection of fields of human computation, eye-tracking and user modeling. In particular, he is interested in automatic assessment of quality of user (study participant) work using eye trackers. He is also interested in user experience studies conduction and support.
|Focuses on information extraction and knowledge discovery from text-based content, by employing ontology engineering and natural language processing. His interests include processing of resources in Slovak language.
||Covers by his research interests the area of web-based systems which utilize concepts of collaboration and collective intelligence, in particular he focuses on knowledge sharing (mainly in Community Question Answering systems) and computer-supported collaborative learning.
|Covers by his research interests the area of user modelling, eye tracking and personalization. He is particularly interested in applying machine learning methods to infer user characteristics (personality traits, cognitive abilities, etc.) using features based on advanced analysis of gaze data and in researching adaptation strategies tailored to individual user differences
Selected recent publications
- KAŠŠÁK, Ondrej - KOMPAN, Michal - BIELIKOVÁ, Mária
Personalized Hybrid Recommendation for Group of Users: Top-N Multimedia Recommender.
Information Processing and Management Journal, Elsevier, Vol.52, No. 3, 2016, pp. 459-477.
- KOMPAN, Michal - BIELIKOVÁ, Mária
Personalized Recommendation for Individual Users Based on the Group Recommendation Principles.
Studies in Informatics and Control, Vol. 22, No. 3, 2013, pp. 331-342.
- SRBA, Ivan - BIELIKOVÁ, Mária
A Comprehensive Survey and Classification of Approaches for Community Question Answering.>
ACM Transactions on the Web, Vol. 10, No. 3, Aug. 2016, pp. 1-63.
ŠIMKO, Jakub - TVAROŽEK, Michal - BIELIKOVÁ, Mária
Human computation: Image Metadata Acquisition based on a Single-player Annotation Game.
International Journal of Human-Computer Studies. Vol. 71, No. 10, 2013, pp. 933-945.
KORENEK, P. - ŠIMKO, Marián
Sentiment Analysis on Microblog Utilizing Appraisal Theory.
World Wide Web Journal. Vol. 17, No. 4, 2014, pp. 847-867.
- ŠIMKO, Jakub - BIELIKOVÁ, Mária
Semantic Acquisition Games: Harnessing Manpower for Creating Semantics.
Semantic Acquisition Games: Harnessing Manpower for Creating Semantics. 1st Ed., Springer, 2014. 141 p.
- KURIC, Eduard - BIELIKOVÁ, Mária
ANNOR: Efficient Image Annotation Based on Combining Local and Global Features.
Computers and Graphics. Vol. 47, No. 2, 2015, pp. 1-15.
- KRAMÁR, Tomáš - BARLA, Michal - BIELIKOVÁ, Mária
Personalizing Search using Socially Enhanced Interest model, Built from the Stream of User's Activity.
Journal of Web Engineering. Vo.12, No. 1-2, 2013, pp. 65-92.
- BIELIKOVÁ, Mária - ŠIMKO, Marián - BARLA, Michal - TVAROŽEK, Jozef - LABAJ, Martin - MÓRO, Robert - SRBA, Ivan - ŠEVCECH, Jakub
ALEF: From Application to Platform for Adaptive Collaborative Learning.
Recommender Systems for Technology Enhanced Learning: Research Trends and Applications. Book Chapter. Springer, 2014, pp. 195-225.
- BIELIKOVÁ, Mária - MÓRO, Robert - ŠIMKO, Jakub - Tvarožek, Jozef
Adaptive Web-Based Textbook Utilizing Gaze Data.
Journal of Eye Movement Research, Vol. 8, No. 4, 252. 2015.
- KRÁTKY, Peter - CHUDÁ, Daniela
Mouse usage biometrics in eLearning systems: detection of impersonation and user profiling.
Int. Journal of human capital and information technology professionals. Vol. 6, No. 1, 2015, PP. 39-50.
- VRABLECOVÁ, Petra - ŠIMKO, Marián
Supporting Semantic Annotation of Educational Content by Automatic Extraction of Hierarchical Domain Relationships.
IEEE Transactions on Learning Technologies. Vol 9, Issue 3, 2016, PP. 285-298.
Important recent research results and research projects
- Part of Centre of Excellence for Smart technologies, Systems and Services; Research of methods for acquisition, analysis and personalized conveying of information and knowledge (2011-2015)
- TraDice (Traveling in Digital Space) - interdisciplinary research project with focus on goal-driven and exploratory search, search with semantics, social aspects of search, personalization and context in digital libraries (2011-2014, http://tradice.fiit.stuba.sk/)
- HIBER (Human Information Behaviour in the Digital Space) - interdisciplinary research project focused on on the research of new models and methods for gathering and processing information for better understanding of human information behaviour in a digital space (2016-2020)
- SCOPES (Innovative teaching curricula, methods and infrastructure for computer science and software engineering) (2015-2018) Institutional partnership project with Switzerland and Serbia: Universita della Svizzera italiana in Lugano and University of Novi Sad.
- Tools developed for research purposes: Annota (service for creating and sharing bookmarks and notes and managing personal library on the Web), ALEF (platform for adaptive collaborative web-based learning), Turing (online programming exercise learning system), Askalot (a novel concept of educational and organizational community question answering system, demo)
- Conversion prediction for major business platform for digital media (behavioral models for predicting conversions of readers info paying customers)
- Personalised recommendation for a discount portal
- TV User behavior analysis for a telecom company
- Platform for TV program recommendation (in collaboration with a media agency and a telecom company)
- News recommendation for major Slovak newspaper (scalability for the real-time, heavily dynamic environment)
- Studies examining user behaviour and user experience during the use of information systems, web/mobile applications and multimedia for several Slovak banks and an e-shop
- Sentiment analysis on a social network in cooperation with a communication and PR agency serving as their customers’ business analysis tool (comprehensive language models employing specifics of social content were trained)
- Askalot - the first educational and organizational CQA system; deployed in collaboration with Harvard University as a part of MOOC system edX (a course with more than 5000 students); used on the additional three universities Europe-wide (Slovak University of Technology in Bratislava; University of Lugano, Switzerland; University of Novi Sad, Serbia)
- Adaptive and collaborative learning platform ALEF (1500 students as users to date, Special prize of the Minister of Education, Science, Research and Sport of the Slovak Republic)
- Faculty of Arts, Comenius University (prof. Jela Steinerová, prof. Jaroslav Šúšol, assoc. prof. Milica Schraggeová, assoc. prof. Anton Heretik, Jr.)
- Faculty of Electrical Engineering and Informatics, Technical University Košice (prof. Ján Paralič)
- Faculty of Informatics, Lugano University (prof. Cesare Pautasso)
- School of Information Sciences, University of Pittsburgh (prof. Peter Brusilovsky)
- Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic (prof. Peter Vojtáš)
- Faculty of Science, University of Novi Sad (prof. Mirjana Ivanovic)
- Eindhoven University of Technology (prof. Paul de Bra)
- Humanities Lab, Lund University (prof. Kenneth Holmqvist)
- User eXperience and Interaction Research Center
- UXI Sensor Lab - 300Hz Tobii TX300 eyetracker for detailed user observation, Tobii stand for mobile devices, neurological sensors (EEG), physiological wireless sensors (ECG, GSR, FSR, temperature), visual analysis, software-based facial expression analysis (HD a 3D camera)
- UXI Group Lab - 20 desktop computer workstations equipped with Tobii X2-60 eyetrackers, software infrastructure for mass data collection (lifecycle of management of research projects, processing of research data, data aggregation from multiple workstations and sources, i.e. eyetracker, mouse, keyboard, camera)
- Data centre – 736 cores, 10TB ram, 100TB disk
- Smart – 16 nodes, 128 cores, 0.6TB ram, 48TB disk
- Graphic card computations:
- GTX 980 Ti – 2816 cores, 4GB DDR5
- 2x GTX 960 – 1024 cores, 4GB DDR5