Pattern recognition and classification for multivariate time series
Stephan Spiegel, Julia Gaebler, Andreas Lommatzsch, Ernesto William De Luca, Şahin Albayrak · 2011
Nowadays we are faced with fast growing and permanently evolving data, including social networks and sensor data recorded from smart phones or vehicles. Temporally evolving data brings a lot of new challenges to the data mining and machine learning community. This paper is concerned with the recognition of recurring patterns within multivariate time series, which capture the evolution of multiple parameters over a certain period of time.