Distance measure for querying sequences of temporal intervals

Time series representations are not always rich enough to describe the temporal activity, for instance, when the context and the relations of the observed elements are of interest. Sequences of temporal intervals use such intervals as primitives in their representation, and allow focusing on the temporal relations of these elements. This is a useful representation of data across many domains. Searching, indexing, and mining such sequences is essential for domain experts in order to discover useful information out of them. In this paper, we formulate the problem of comparing sequences of temporal intervals and propose a novel distance measure. We discuss the properties of the measure and study its robustness in the domain of sign language. Experiments on real data show that the measure is robust in terms of retrieval accuracy even for high levels of artificially introduced distortion.

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