Search for dissertations about: "data reduction"
Showing result 1 - 5 of 1722 swedish dissertations containing the words data reduction.
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1. Algorithmically Guided Information Visualization : Explorative Approaches for High Dimensional, Mixed and Categorical Data
Abstract : Facilitated by the technological advances of the last decades, increasing amounts of complex data are being collected within fields such as biology, chemistry and social sciences. The major challenge today is not to gather data, but to extract useful information and gain insights from it. READ MORE
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2. Flood Hazard Assessment in Data-Scarce Basins : Use of alternative data and modelling techniques
Abstract : Flooding is of great concern world-wide, causing damage to infrastructure, property and loss of life. Low-income countries, in particular, can be negatively affected by flood events due to their inherent vulnerabilities. Moreover, data to perform studies for flood risk management in low-income regions are often scarce or lacking sufficient quality. READ MORE
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3. On Adapting Data Collection to Intrusion Detection
Abstract : Intrusion detection systems (IDSs) are capable of detecting both suspicious insider activity and attacks from external penetrators. They can also detect both known and previously unknown attacks. These capabilities make them valuableassets in the protection of computer systems and networks. READ MORE
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4. Aspects of Adapting Data Collection to Intrusion Detection
Abstract : The focus of this thesis is on data collection and in particular data collection for intrusion detection purposes. Data collection is the first, and possibly most important activity in the overall intrusion detection process. The result of the detection can never be better than the data on which the detection is based. READ MORE
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5. Online Dimensionality Reduction
Abstract : In this thesis, we investigate online dimensionality reduction methods, wherethe algorithms learn by sequentially acquiring data. We focus on two specificalgorithm design problems in (i) recommender systems and (ii) heterogeneousclustering from binary user feedback. READ MORE