Abstract. Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the ...
Forecasting airborne pollen concentrations is one of the most studied topics in aerobiology, due to its crucial application to allergology. The most used tools for this problem ar...
Most time series comparison algorithms attempt to discover what the members of a set of time series have in common. We investigate a di erent problem, determining what distinguish...
Similarity search in time series data is an active area of research in data mining. In this paper we introduce a new approach for performing similarity search over time series dat...
This article proposes knowledge-based short-time prediction methods for multivariate streaming time series, relying on the early recognition of local patterns. A parametric, well-i...