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 …

Applications of smart environments are ever-increasing due to their possibilities of
contributing towards an independent and active lifestyle for different user groups. An …

In this paper, we study the problem of classification of sequences of temporal intervals. Our
main contribution is the STIFE framework for extracting relevant features from interval …

In several application domains, including sign language, sensor networks, and medicine,
events are not necessarily instantaneous but they may have a time duration. Such events …

Speech and singing voice discrimination is an important task in the speech processing area
given that each type of voice requires different information retrieval and signal processing …

Given a social network with dynamic interactions, how can we discover frequent interactions
between groups of entities? What are the temporal patterns exhibited by these interactions …

We study the problem of online similarity search in sequences of temporal intervals; given a
standing query and a time-evolving sequence of event-intervals, we want to assess the …

Previous works of subsequence search in time interval-based events sequences have
focused on the relations among events without considering the duration of each event …

In this paper we present a novel method for automatic segmentation of speech and
monophonic singing voice based only on two parameters derived from pitch: proportion of …

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 …