Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"temporal data mining"”.
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Temporal Data Mining in a Dynamic Feature Space
Many interesting real-world applications for temporal data mining are hindered by concept drift. One particular form of concept drift is characterized by changes to the underlying feature space. Seemingly little has been done to address this issue. This thesis presents FAE, an incremental ensemble …
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Towards Algorithm Transformation for Temporal Data Mining on GPU
Data Mining allows one to analyze large amounts of data. With increasing amounts of data being collected, more computing power is needed to mine these larger and larger sums of data. The GPU is an excellent piece of hardware with a compelling price to performance ratio and has rapidly risen in …
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Semantics orientated spatial temporal data mining for water resource decision support
… heavily on computer software processing to help data queries for common and rare patterns for analyzing critical water events. For example, it is vital for decision makers to know if certain types of water quality problems are isolated (e.g. rare) or ubiquitous (e.g. common) and whether the …
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Alarm management: Mining for groups of co-occuring alarm tags
… as chemical plants and petroleum refineries have databases with the ability to store terabytes of data. While it is possible to manually extract the information required for alarm rationalization, the extensive quantity and complexity of data has made the analysis and decomposition a very …
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A method to detect and represent temporal patterns from time series data and its application for analysis of physiological data streams
… rate thus generating significant amounts of data every second. This results to more than 2 million records generated per patient in an hour. It’s an immense challenge for anyone trying to utilize this data when making critical decisions about patient care. Temporal abstraction and data mining …
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Multiple Uses of Frequent Episodes in Temporal Process Modeling
… investigates algorithmic techniques for temporal process discovery in many domains. Many different formalisms have been proposed for modeling temporal processes such as motifs, dynamic Bayesian networks and partial orders, but the direct inference of such models from data has been …
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Scalable data analytics techniques for summarizing spatial network-based observations
… or representation of large spatial or spatio-temporal datasets. For example, transportation planners and engineers may need to identify road segments that pose risks for pedestrians and require redesign. However, SSNO is computationally challenging for the following reasons: (1) There may be a …