Title Turinio filtras, paremtas daugialypės terpės failų klasifikavimu /
Translation of Title Content filter based on classification of multimedia documents.
Authors Mečkauskas, Edgaras
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Pages 77
Abstract [eng] An algorithm, able to solve two class problem, designed to analyse and classify multimedia documents such as HTML pages by using textual content, is suggested in the paper. Moreover, content filter based on Mozilla Firefox extension was developed to classify web pages according to the algorithm. Linear support vector machine (SVM) was developed using PHP programming language in order to train the classifier. The main advantage of the content filter we developed which distinguishes it from other analogical tools existing in the market is its ability to classify web pages unfamiliar to the algorithm and to block a part or entire web document depending on setup.
Type Master thesis
Language Lithuanian
Publication date 2014