Automatic taxonomy generation: Issues and possibilities
Raghu Krishnapuram, Krishna Kummamuru
IFSA 2003
This work motivates the need for more flexible structural similarity measures between time-series sequences, which are based on the extraction of important periodic features. Specifically, we present non-parametric methods for accurate periodicity detection and we introduce new periodic distance measures for time-series sequences. We combine these new measures with an effective metric tree index structure for efficiently answering k-Nearest-Neighbor queries. The goal of these tools and techniques are to assist in detecting, monitoring and visualizing structural periodic changes. It is our belief that these methods can be directly applicable in the manufacturing industry for preventive maintenance and in the medical sciences for accurate classification and anomaly detection. © 2005 Springer Science+Business Media, Inc.
Raghu Krishnapuram, Krishna Kummamuru
IFSA 2003
B. Wagle
EJOR
Michael D. Moffitt
ICCAD 2009
Douglas W. Cornell, Daniel M. Dias, et al.
IEEE Transactions on Software Engineering