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Index Suitable for Similar Search in High-dimensional Spaces
Krejčová, Martina ; Kopecký, Michal (advisor) ; Skopal, Tomáš (referee)
In this paper, we focus on indexing and searching in high-dimensional data. To achieve the target we implemented the Metric Index, a model of the similarity search based on the metric spaces, that employs many of known principles of partitioning and filtering. The metric space is a general model of similarity, which enables the usage of implemented index for various data. With this index, stored data could be searched effectively. The internal structure of data is hidden, we just require an implementation of the function for feature extraction, which produces a vector representing data, and the metric function applicable to the given data. The Metric Index was implemented as a data cartridge, the mechanism for extending the capabilities of the Oracle server. This data cartridge enables indexing of large unstructured data in the Oracle server known as LOBs.
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Similarity search in image collections
Navrátil, Lukáš ; Bartoš, Tomáš (advisor) ; Skopal, Tomáš (referee)
Detection of keypoints from image and their characterization by using descriptors is common technique in some branches of computer vision. The goal of this thesis is to explore and confirm usability of this technique for similarity retrieval in image collections. For this purpose it will be created a web application used for collecting ratings of similarity from users which will be subsequently compared with results computed by the implementation of SURF algorithm, one of algorithms used for detection and description of image keypoints. It will also be discussed the impact of metrics and parameters influencing results of computation of similarity between images and it will be made an effort to find settings for which computed results will be closest to user's similarity perception.
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Automatically Updated Bibliography
Valo, Boris ; Škoda, Petr (referee) ; Smrž, Pavel (advisor)
This paper describes the development of application for automatically updated bibliography. Nowadays, many Internet users search informations they need, this is important especially in sets of scientific publications and articles. The aim of this thesis is convenient tool for users to create their own portal. This is achieved by storing documents and their subsequent search using ElasticSearch. Retrieval is made by Boolean queries and additional search using similarity search tool MoreLikeThis. At the end of this thesis is described the way of testing and evaluation of retrieval.
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