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Semi-Markov kMeans Clustering and Activity Recognition from Body-Worn Sensors

Robards, Matthew; Sunehag, Peter


Subsequence clustering aims to find patterns that appear repeatedly in time series data. We introduce a novel subsequence clustering technique that we call semi-Markov kmeans clustering. The clustering results in ideal examples of the repeating patterns and in labeled segmentations that can be used as training data for sophisticated discriminative methods like max-margin semi-Markov models. We are applying the new clustering technique to activity recognition from body-worn sensors by showing...[Show more]

CollectionsANU Research Publications
Date published: 2009
Type: Conference paper
Source: Proceedings of the IEEE International Conference on Data Mining (ICDM 2009)
DOI: 10.1109/ICDM.2009.13


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