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Knowledge representation for expert systems
Lekeš, Pavel ; Sáblík, Václav (referee) ; Polách, Petr (advisor)
The objective of this work is to analyze using of the first order logic for reasoning in knowledge based systems. Merit of the predicate logic is its relative simplicity in matter of algorithm development, where it is possible to decide about validity of a sentence written in first order logic language, by using formal rules without any connection to real meanings of logical variables. In Expert systems, the first order logic is used to derivate new formulas from given axioms, where previously derived formulas are included to the axioms as well. Its process of derivation of implicit believes from explicitly given facts.
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Expert systems ES for home study and evaluation
Novák, Jaroslav ; Honzík, Petr (referee) ; Jirsík, Václav (advisor)
This master thesis contains the basic information about knowledge and expert systems. The thesis contains theoretic text about architecture of the expert systems and representation knowledge. The text regarding on representation knowledge contains examples of different ways of knowledge representation for expert systems. In the next part is described the design and all functions of the expert systems. This expert system uses frames representation.
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Fuzzy Petri Nets for Expert systems
Maksant, Jindřich ; Valenta, Jan (referee) ; Jirsík, Václav (advisor)
The object of this thesis is proposal and practical implementation of expert system, whose knowledge base will be modeling by fuzzy Petri nets. The proposal is based on knowledge in theoretical analysis of diagnostic expert system and fuzzy Petri nets. This proposal is realised in programming language C#. There are described functions of program and it is made a model consultation with using two different knowledge base.
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Expert systems
Veselovský, Michal ; Konečný, Pavel (referee) ; Dvořák, Jiří (advisor)
Expert systems (ES) are commercially one of the most succesfull use of artificial intelligence (AI) - since eighties of the 20th century. They are often used in medicine, industry, science, trade, banking etc. Expert system is a software using knowledge of human experts for solving very complicated tasks and problems, which would otherwise require participating or consultation of one or more specialists on these issues. This software simulates decision-making of human expert in solving complicated tasks, and tries to reach the most probable result, ideally same as the expert´s opinion. Typical feature of expert systems, differencing it from usual software, is separating of decision making engine (inference engine) and knowledge base – same expert system with different knowledge base may serve for different purposes. This feature is used for creating empty expert systems – shells. Other features, which may not occur at all ES, are ability to make decision with uncertainty, and ability to explain the decision. Goal of this work is to describe basic principles of ES, using freely available information sources, and then describe and analyze resources for creating of these systems, using mainly information from official web sites.
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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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