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Content Based Image Search with Vector Quantization
Snášel, V. ; Húsek, Dušan
Fast and efficient query of information based on image contents is one of the major challenges in visual information systems. Features pace based the Vector Quantization (VQ). The indexing system extracts VQ features from each image to be inserted in the database. The size of the feature vector is much smaller than the image size but the feature vector accurately represents the image.
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Effective methods of plagiarism detectios in large document repositories
Přibil, Jiří ; Jiroušek, Radim (advisor) ; Strossa, Petr (referee) ; Snášel, Václav (referee)
The work focuses on issues of plagiarism detection in large document repositories. Taking into account real situation that needs to be addressed now in the university environment in the Czech Republic and proposes a system that will be able to carry out this analysis in real time and yet be able to capture the widest possible range of plagiarism methods. The main contribution of this work is taking the definition of so-called unordered n-grams - {n}-grams - which can be used just to detect some forms of advanced plagiarism methods. All cited recommendations that relate to the various components of the system to detect plagiarism - preprocessing the document before document insertion into the corpus, the representation of documents in document storage, identification of potential sources of plagiarism to calculate rates of similarity; visualization analysis of plagiarism - are subject to discussion and appropriately quantified. The result is a set of design parameters of the system so that it can in detect plagiarism in the Czech language language quickly, accurately and yet in most forms.
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Ontology Learning and Information Extraction for the Semantic Web
Kavalec, Martin ; Berka, Petr (advisor) ; Štěpánková, Olga (referee) ; Snášel, Václav (referee)
The work gives overview of its three main topics: semantic web, information extraction and ontology learning. A method for identification relevant information on web pages is described and experimentally tested on pages of companies offering products and services. The method is based on analysis of a sample web pages and their position in the Open Directory catalogue. Furthermore, a modfication of association rules mining algorithm is proposed and experimentally tested. In addition to an identification of a relation between ontology concepts, it suggest possible naming of the relation.
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