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Web graphic knowledge base editor for expert system NEST
Kozák, Martin ; Zamazal, Ondřej (advisor) ; Berka, Petr (referee)
Main goal of this thesis is development of knowledge base editor designed to work online. Such editor would provide its user with all tools that are necessary to create and modify knowledge base in a graphic and user-friendly working environment. This editor is developed for system NEST (New Expert SysTem), which is an expert system developed on University of Economics, Prague. Created editor is named WEBZ it is created as a web application. WEBZ is written in Java and build on Vaadin framework. Vaaadin is a framework created to develop web application while supporting a creation of graphic user interface. The thesis first chapter is a theoretical introduction into expert systems with a brief description of NEST. The description of NEST continues in second chapter, which is focused on a knowledge base of this expert system. In the following chapter, Vaadin framework is briefly described. The thesis continues with the comparison between WEBZ and its predecessors. Last two chapters are dedicated to description of WEBZ both from the perspective of user and from the perspective of developer.
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Electronic financial reporting
Kapusta, Michal ; Mejzlík, Ladislav (advisor) ; Pelák, Jiří (referee)
This thesis explores current and future possible uses of ICT in financial reporting, describes the properties, usage and implementation of EDI and XBRL, describes the concept of online reporting and continuous auditing, introduces the area of artificial intelligence and expert systems and their application in accounting and auditing, describes development and application of FRAANK for extraction of financial data from EDGAR repository, describes the implementation of continuous auditing in Siemens and finally states the possible reasons, why the technologies are not used to their full potential.
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Extrakce informací z webových stránek pomoci extrakčních ontologií
Labský, Martin ; Berka, Petr (advisor) ; Strossa, Petr (referee) ; Vojtáš, Peter (referee) ; Snášel, Václav (referee)
Automatic information extraction (IE) from various types of text became very popular during the last decade. Owing to information overload, there are many practical applications that can utilize semantically labelled data extracted from textual sources like the Internet, emails, intranet documents and even conventional sources like newspaper and magazines. Applications of IE exist in many areas of computer science: information retrieval systems, question answering or website quality assessment. This work focuses on developing IE methods and tools that are particularly suited to extraction from semi-structured documents such as web pages and to situations where available training data is limited. The main contribution of this thesis is the proposed approach of extended extraction ontologies. It attempts to combine extraction evidence from three distinct sources: (1) manually specified extraction knowledge, (2) existing training data and (3) formatting regularities that are often present in online documents. The underlying hypothesis is that using extraction evidence of all three types by the extraction algorithm can help improve its extraction accuracy and robustness. The motivation for this work has been the lack of described methods and tools that would exploit these extraction evidence types at the same time. This thesis first describes a statistically trained approach to IE based on Hidden Markov Models which integrates with a picture classification algorithm in order to extract product offers from the Internet, including textual items as well as images. This approach is evaluated using a bicycle sale domain. Several methods of image classification using various feature sets are described and evaluated as well. These trained approaches are then integrated in the proposed novel approach of extended extraction ontologies, which builds on top of the work of Embley [21] by exploiting manual, trained and formatting types of extraction evidence at the same time. The intended benefit of using extraction ontologies is a quick development of a functional IE prototype, its smooth transition to deployed IE application and the possibility to leverage the use of each of the three extraction evidence types. Also, since extraction ontologies are typically developed by adapting suitable domain ontologies and the ontology remains in center of the extraction process, the work related to the conversion of extracted results back to a domain ontology or schema is minimized. The described approach is evaluated using several distinct real-world datasets.
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Possibilistic Laws of Large Numbers
Kramosil, Ivan
We consider sequences of samples defined on spaces endowed by a possibilistic measure, looking for relatively small sets of such sequences which are important or interesting, in a sense, and which occur with possibility degree equal to one or tending to one with the length of the sample sequence increasing.
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Possible trends in the progress of using ICT in the Accounting
Ďurianová, Gabriela ; Mejzlík, Ladislav (advisor) ; Velechovská, Lenka (referee)
My thesis addresses to matters of rising connectedness of Accounting and Information Technologies. It describes history of forms and techniques used in Accounting and also the possibilities and trends of Applied Informatics used nowadays in this field. The text accents to efforts of making the process of accounting more effective by reducing the cost, improving the quality and by shortening the time it can be done. The part of my thesis also mentions the level of regulation of the techniques used for processing the accounting from the point of view of national norms and also of International standards.
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