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Abstract. The increasing availability of massive mobile phone call data records (CDR) has opened new opportunities for analyzing and understanding real-life social phenomena and human dynamics. In order to better interpret this enormous amount of data it is useful to contextualize them with information about the circumstances under which they has been generated. Nowadays, linked open data initiative provide access to a huge amount of geo-time referenced knowledge about territory and events that happen in the territory. These informations can be used to characterize the aforementioned context. The aim of this Ph.D is to investigate on the intercorrelations between CDR, contexts, and human behaviors. The ultimate goal is to build a stochastic model, that can be used to predict semantic (qualitative) behavioral patterns on the basis of CDR traffic and context and identify and explain anomalous situations on the basis of deviations from standard CDR patterns.
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Stored only when both papers are in the corpus — 5 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.