-------------------------------------------------------------------- COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER AND THE SCHOOL OF PHYSICS, ASTRONOMY, & COMPUTATIONAL SCIENCES (CSI 898-Sec 001) -------------------------------------------------------------------- Time Series Data Mining and Pattern Discovery Jessica Lin Computer Science Department, George Mason University, Fairfax, VA Massive amounts of data are generated daily at a rapid rate. As a result, the world is faced with unprecedented challenges and opportunities on managing the ever-growing data, and much of the world's supply of data is in the form of time series. One obvious problem of handling time series databases concerns with its typically massive size. Most classic data mining algorithms do not perform or scale well on time series data due to their unique structure. In particular, the high dimensionality, very high feature correlation, and the typically large amount of noise that characterize time series data present a difficult challenge. As a result, time series data mining has attracted an enormous amount of attention in the past two decades. This presentation gives an overview of my contributions in the field of time series data mining. The first part of the presentation discusses time series data mining fundamentals - more specifically, the two aspects that hugely determine the efficiency and effectiveness of most time series data mining algorithms: data representation and similarity measure. The second part of the presentation will focus on the discovery of novel and non-trivial patterns in time series data, including frequently encountered (or repeated) patterns, rare (or anomalous) patterns, contrasting patterns and latent structure. March 23, 2015 4:30 pm Exploratory Hall, room 3301, Fairfax Campus Refreshments will be served at 4:15 PM. ---------------------------------------------------------------------- Find the schedule at http://www.cmasc.gmu.edu/seminars.htm