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Computer Science Seminar - Grammar-Based Time Series Pattern Mining and Visualization
(Greater Washington DC Metro Area)
Jessica Lin, associate professor in the Department of Computer Science at George Mason University, will present "Grammar-Based Time Series Pattern Mining and Visualization."
This talk will focus on the discovery of novel and non-trivial patterns in time series data, including frequently encountered patterns (motifs) and rare patterns (anomalies). The ability to efficiently detect frequent and anomalous patterns in time series allows for the exploration, summation, and compression of data.
Her recent work demonstrates that grammar induction, the process of learning rules of a formal language from a set of observations, allows the discovery of hierarchical structures and regularities from input time series. Lin will also discuss GrammarViz, an interactive tool for grammar-driven mining and visualization of variable-length time series patterns.
Lin received her Ph.D. from he University of California, Riverside, in 2005. Her research interests encompass broad areas of data mining and machine learning on large-scale multimedia datasets including time series, spatiotemporal databases, text, and images. Her research is partially funded by the National Science Foundation; U.S. Army; Naval Research Lab; and Intel Corporation.
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