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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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Fuzzy GUHA
Ralbovský, Martin ; Rauch, Jan (advisor) ; Svátek, Vojtěch (referee) ; Holeňa, Martin (referee) ; Vojtáš, Peter (referee)
The GUHA method is one of the oldest methods of exploratory data analysis, which is regarded as part of the data mining or knowledge discovery in databases (KDD) scienti_c area. Unlike many other methods of data mining, the GUHA method has firm theoretical foundations in logic and statistics. In scope of the method, finding interesting knowledge corresponds to finding special formulas in satisfactory rich logical calculus, which is called observational calculus. The main topic of the thesis is application of the "fuzzy paradigm" to the GUHA method By the term "fuzzy paradigm" we mean approaches that use many-valued membership degrees or truth values, namely fuzzy set theory and fuzzy logic. The thesis does not aim to cover all the aspects of this application, it emphasises mainly on: - Association rules as the most prevalent type of formulas mined by the GUHA method - Usage of fuzzy data - Logical aspects of fuzzy association rules mining - Comparison of the GUHA theory to the mainstream fuzzy association rules - Implementation of the theory using the bit string approach The thesis throughoutly elaborates the theory of fuzzy association rules, both using the theoretical apparatus of fuzzy set theory and fuzzy logic. Fuzzy set theory is used mainly to compare the GUHA method to existing mainstream approaches to formalize fuzzy association rules, which were studied in detail. Fuzzy logic is used to define novel class of logical calculi called logical calculi of fuzzy association rules (LCFAR) for logical representation of fuzzy association rules. The problem of existence of deduction rules in LCFAR is dealt in depth. Suitable part of the proposed theory is implemented in the Ferda system using the bit string approach. In the approach, characteristics of examined objects are represented as strings of bits, which in the crisp case enables efficient computation. In order to maintain this feature also in the fuzzy case, a profound low level testing of data structures and algoritms for fuzzy bit strings have been carried out as a part of the thesis.
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Incorporation of Agent Oriented Approaches to the Complex Process Description Methodology
Smolík, Jan ; Řepa, Václav (advisor) ; Vojtáš, Peter (referee) ; Bukovský, Ivo (referee)
The main objective of this thesis is to integrate agent oriented concepts into a complex methodology for description of business processes MMABP that is being developed on University of Economics, Prague. The first part describes and explains agent oriented approaches to business process modeling (i*/TROPOS, AOR, OOEM and UFO ontology) and demonstrates them on a case study. MMABP methodology is then compared with these approaches and evaluated. The evaluation concludes that MMABP is incomplete in relation to agent oriented concepts of plan, plan execution, desire, intention, commitment and claim and also to concepts of stable and unstable state. Concepts of goal, agent and business process are evaluated as inaccurate. Second part of the theses arguments and defines MMABP extension that eliminates identified inadequacies. Metamodel is amended with the concept of plan execution which is intentionally executed action that leads to a goal fulfillment. Plan is a description of this special kind of action. Agent is an entity that has goals and is capable of executing plans. Business process received a new definition and is defined as something that defines plans (as a prescription of actions), has goals and uses agents to execute actions. Business process is not defined as a specialization of a complex event anymore. The thesis also specifies procedure where concepts are step-by-step transformed from one diagram to another.
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Experimenty s českými lingvistickými daty a ILP
Dědek, Jan ; Eckhardt, Alan ; Vojtáš, Peter
In this paper we present basic experiments that we have made in connection with our research in the domain of the Semantic Web. These experiments should demonstrate possibilities of employing ILP technique in the task of acquisition of semantic information from text of Czech Web pages. These experiments are preceded by complex linguistic analysis of the texts and the output of linguistic tools is processed in the ILP procedure.
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Semantic web
Dědek, J. ; Eckhardt, Alan ; Galamboš, L. ; Vojtáš, Peter
The paper is an overview of possibilities of sematic web, its potential, problems and possible solutions. It cover some aspects - how to obtain structured data, how to quickly process web pages and how to design a simple agent that will make use of such possibilities of semantic web.
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User Preferences for Searching in Web Sources
Eckhardt, Alan ; Vojtáš, Peter
Main topic of this paper are user preferences in sematic web environment. We describe a model for querying with user preferences upon RDF data and for ordering of the answer by user aggregation function. Our model has a theoretical base in modification of fuzzy description logic, which is embedable into two-value description logic and extends OWL. We desceribes also experiments, which were done using framework for flexible querying Tokaf. We extended standard algorithms for searching k bet answers, using new heuristics. These heuristics were also tested
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