14 Octobre - 20 Octobre

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Jeudi 17 Octobre
Heure: 14:00 - 16:00
Lieu: Salle B107, bâtiment B, Université de Villetaneuse
Résumé: Explicative Data Analytics
Description: Martin Atzmüller Modeling and mining multi-modal and heterogeneous data is important in the context of analyzing knowledge and information processes in complex environments, e.g. for mining high dimensional and heterogeneous (sensor) data, the analysis of exceptional patterns, and complex network structures. For making sense of the data, explicative data analytics focuses on interpretable, transparent and explainable approaches, which is relevant for very many applications for analyzing data in science and industry. The talk presents according approaches for explicative data analytics incorporating methods from data science, machine learning, and human computing, exemplified by multi-modal sensor data analysis, pattern mining and graph analytics.