Abstract Qualitative Spatial & Temporal Reasoning (QSTR) is a major field of study in
Symbolic AI that deals with the representation and reasoning of spatiotemporal information …

In this paper, we study the problem of classification of sequences of temporal intervals. Our
main contribution is a novel framework, which we call SMILE, for extracting relevant features …

Symbolic Time Intervals (STIs) represent events having a non-zero time duration, which are
common in various application domains. In this article, we focus on the challenge of STIs …

Classification of sequences of temporal intervals is a part of time series analysis which
concerns series of events. We propose a new method of transforming the problem to a task …

Event-interval sequences are defined as multivariate series of events that occur over time.
The classification of event-interval sequences has gained increasing attention among …

Large, varied, and time-evolving data sources can be observed across many domains and
present a unique challenge for classification problems, in which traditional machine learning …