Home » Talks and Events » 2007 » Initiative in Innovative Computing @ Harvard - Seminar Series - Prof. Eamonn Keogh
Initiative in Innovative Computing @ Harvard
The Initiative in Innovative Computing fosters the creative use of computational resources to address issues at the forefront of data-intensive science. Focusing on interdisciplinary collaborations that span traditional academic boundaries, the IIC fosters the flow of ideas and inventions along the continuum from basic science to scientific computation to computational science to computer science.
February 14, 2007 - Cambridge - Massachusetts - USA 
This is one of the seminars organized by the Initiative in Innovative Computing @ Harvard.
To date, the vast majority of research on time series and shape data mining has focused on similarity search and clustering. I believe that these problems should now be regarded as essentially solved. In particular, there are now fast exact techniques for searching and clustering patterns under both the Euclidean distance and Dynamic Time Warping, the two most useful distance measures. However, from a knowledge discovery viewpoint, there are much more interesting problems, the detection of previously unknown patterns and relationships in time series and shape databases. Two concrete examples are finding the most unusual objects (discord discovery) and finding repeated objects (motif discovery).
While there are many representations that can be used to solve these problems (i.e. wavelets, Fourier methods etc), in this talk I argue that solutions which are scalable to massive datasets will require symbolic representations. The talk will be illustrated with examples from anthropology, law enforcement, biology and mining of historical texts.
