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.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:305074 |
| Date | January 2012 |
| Creators | Krejčová, Martina |
| Contributors | Kopecký, Michal, Skopal, Tomáš |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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