A multi-scale methodology for explaining data streams

author: Luka Stopar, Artificial Intelligence Laboratory, Jožef Stefan Institute
published: Oct. 21, 2015,   recorded: October 2015,   views: 1624
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This paper presents a novel, multi-scale, framework, for the simultaneous analysis of multiple data streams, called StreamStory. The framework models the data streams as a hierarchical Markovian model by automatically learning states and transitios, and aggregating them into a hierarchy of Markov chains. This approach aims to compensate the gap between lowlevel streaming observations and high-level output/alerts which provide a value for higher levels of streaming data analysis, like inference and prediction, and provides ground for qualitative interpretation of the data.

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