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Design and Implementation of System for Aggregations of Real Estate Offers in the Czech Republic
Drobník, Jakub ; Kučera, Jan (advisor) ; Chlapek, Dušan (referee)
The diploma thesis deals with the design and implementation of software for aggregations of real estate offers in the Czech Republic. The aim of the thesis is to create a system which aggregates the data of real estate offers from web pages. This thesis consists of two basic parts. The context of creating the system is described in the first part. The author discusses ways to retrieve data from websites - especially the extraction of data using automated robots - in the first part of the thesis. The design and implementation of the system are described in the second part. The author and sponsor define requirements for the system in the second part of the thesis. The outcome of this thesis is a prototype that aggregates data from real estate portals into the prepared database. The main contribution of the thesis is an example of a possible approach that can aggregate data from a particular market segment and put it into the database.
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Web page data figure finder
Janata, Dominik ; Vojtáš, Peter (advisor) ; Nečaský, Martin (referee)
The thesis treats automatic extraction of semantic data from Web pages. Within this broad problem, it focuses on finding values of data figures within the page presenting certain entity (e.g. price of a laptop). The main idea we wanted to evaluate is that a figure can be found using its context in the page: the words that surround it and values of the attributes of the containing HTML tags, class attribute in particular. Our research revealed there are two types of contemporary solutions of this problem: either the author of the Web page must inline semantic information inside the markup of the page or there are commercial tools that can be trained to parse a particular page format (targetting pages from a single Web domain). We examined the possibilities of developing a general solution that would - for given entity - find its properties across the Web domains using text analysis and machine learning. The naïve algorithm had about 30% accuracy, the lear- ning algorithms had the accuracy between 40 and 50% in finding the properties. Despite the accuracy is not acceptable for a final solution, we believe it confirms the potential of the idea. Keywords: Web pages data extraction 1
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Extracting Linked Data from Excel Files
Dembinný, Šimon ; Nečaský, Martin (advisor) ; Bednárek, David (referee)
Title: Extracting Linked Data from Excel files Author: Šimon Dembinný Department: Department of Software Engineering Supervisor of the bachelor thesis: Mgr.Martin Nečaský, Ph.D, Department of Software Engineering at Faculty of Mathematics and Physics of Charles University Abstract: The major part of the thesis rests in the development of an application for extracting Linked Data from Excel files. The application is created as Microsoft Excel Add-on. The comparison with best freely available tool for Linked Data extraction from table data "Open refine" is provided in the theoretical part together with explanation of the concept of Linked Data itself.
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Image object detection using template
Novák, Pavel ; Mašek, Jan (referee) ; Burget, Radim (advisor)
This Thesis is focused to Image Object Detection using Template. Main Benefit of this Work is a new Method for sympthoms extraction from Histogram of Oriented Gradients using set of Comparators. In this used Work Methods of Image comparing and Sympthoms extraction are described. Main Part is given to Histogram of Oriented Gradients Method. We came out from this Method. In this Work is used small training Data Set (100 pcs.) verified by X-Validation, followed by tests on real Sceneries. Achieved success Rate using X-Validation is 98%. for SVM Algorithm.
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