Jan Žižka

Jan Žižka is an Associate Professor at the Department of Informatics, Faculty of Business and Economics, Mendel University Brno, member of SoNet research center, editor-in-chief of International Journal of Information Sciences and Techniques (IJIST), and International Journal of Computer Science & Information Technology (IJCSIT), a member of editorial boards and program committees of several other international scientific journals and conferences. He is also an author and co-author of many journal and conference peer-reviewed articles, and co-editor of several books in the area of informatics. His research areas include artificial intelligence, machine learning, and text/data mining.

Publications

Using Online Data in Predicting Stock Price Movements: Methodological and Practical Aspects
Using Online Data in Predicting Stock Price Movements: Methodological and Practical Aspects
František Dařena, Jonáš Petrovský, Jan Přichystal, Jan Žižka. © 2021. 28 pages.
A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital...
Using Online Data in Predicting Stock Price Movements: Methodological and Practical Aspects
Using Online Data in Predicting Stock Price Movements: Methodological and Practical Aspects
František Dařena, Jonáš Petrovský, Jan Přichystal, Jan Žižka. © 2019. 35 pages.
A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital...
Semantics-Based Document Categorization Employing Semi-Supervised Learning
Semantics-Based Document Categorization Employing Semi-Supervised Learning
Jan Žižka, František Dařena. © 2017. 29 pages.
The automated categorization of unstructured textual documents according to their semantic contents plays important role particularly linked with the ever growing volume of such...
Revealing Groups of Semantically Close Textual Documents by Clustering: Problems and Possibilities
Revealing Groups of Semantically Close Textual Documents by Clustering: Problems and Possibilities
František Dařena, Jan Žižka. © 2017. 40 pages.
The chapter introduces clustering as a family of algorithms that can be successfully used to organize text documents into groups without prior knowledge of these groups. The...
Modern Computational Models of Semantic Discovery in Natural Language
Modern Computational Models of Semantic Discovery in Natural Language
Jan Žižka, František Dařena. © 2015. 335 pages.
Language—that is, oral or written content that references abstract concepts in subtle ways—is what sets us apart as a species, and in an age defined by such content, language has...
Revealing Groups of Semantically Close Textual Documents by Clustering: Problems and Possibilities
Revealing Groups of Semantically Close Textual Documents by Clustering: Problems and Possibilities
František Dařena, Jan Žižka. © 2015. 41 pages.
The chapter introduces clustering as a family of algorithms that can be successfully used to organize text documents into groups without prior knowledge of these groups. The...
Semantics-Based Document Categorization Employing Semi-Supervised Learning
Semantics-Based Document Categorization Employing Semi-Supervised Learning
Jan Žižka, František Dařena. © 2015. 29 pages.
The automated categorization of unstructured textual documents according to their semantic contents plays important role particularly linked with the ever growing volume of such...
Automatic Categorization of Reviews and Opinions of Internet E-Shopping Customers
Automatic Categorization of Reviews and Opinions of Internet E-Shopping Customers
Jan Žižka, Vadim Rukavitsyn. © 2013. 10 pages.
E-shopping customers, blog authors, reviewers, and other web contributors can express their opinions of a purchased item, film, book, and so forth. Typically, various opinions...
Discovering Opinions from Customers’ Unstructured Textual Reviews Written in Different Natural Languages
Discovering Opinions from Customers’ Unstructured Textual Reviews Written in Different Natural Languages
Jan Žižka, František Darena. © 2013. 23 pages.
Gaining new and keeping existing clients or customers can be well-supported by creating and monitoring feedbacks: “Are the customers satisfied? Can we improve our services?” One...
Automatic Categorization of Reviews and Opinions of Internet: E-Shopping Customers
Automatic Categorization of Reviews and Opinions of Internet: E-Shopping Customers
Jan Žižka, Vadim Rukavitsyn. © 2011. 10 pages.
E-shopping customers, blog authors, reviewers, and other web contributors can express their opinions of a purchased item, film, book, and so forth. Typically, various opinions...