Clustering Sequences of Multi-dimensional Sets of Semantic Elements

The study of semantic aspects of human behavior is an hot topic. Most of the time, semantic sequences describe these complex behaviors. Indeed, sequences include several information as type of human activities or places. To study these complex data, we need to define new similarity measures and select appropriate clustering processes. This article proposes a semantic similarity measure, based on ontologies, which manages complex semantic elements with different levels of detail and incertitude. An application of this approach from the domain of touristic mobility shows the interest of this process.