Towards Data Science: From Data to Patterns to Knowledge

12.07.2019 von 14:00 bis 14:00

Recent advances of sensor technologies and the new user mentality of generating and voluntarily sharing information produce a tremendous source of rich data. This data contains information which is very useful for an incredible number of applications enhancing studies for diverse fields of science, supporting the productivity in industry, and enabling advanced services for our society. A necessary building block for taking advantage from this vast amount of information is the development of efficient and effective searching and mining algorithms which is very challenging because of the

specific characteristic of the data that is often unstructured or complex structured, heterogeneous, dynamic, uncertain or incomplete.

Furthermore, entities in our real world need to be considered as a set of interacting or interrelated, multi-typed components. To make such data useful for diverse applications, advanced methods for managing and retrieving information, pattern mining, machine learning and knowledge discovery that can cope with the afore mentioned characteristic of data are necessary. In my talk, I will address some of these issues in the context of scientific applications. In addition, I will introduce current research activities on heterogeneous information networks for cross-domain data fusion and analysis with an outlook to future research opportunities.

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