Project information

Project information
Big Data Analytics for Unstructured Data (Big Data Analytics for Unstructured Data)

Investor logo
Project Identification
Project Period
1/2016 - 12/2018
Investor / Pogramme / Project type
Czech Science Foundation
MU Faculty or unit
Faculty of Informatics

Development of new foundations for Big Data Analytics requires an effective and efficient content-based access to data that is prevalently unstructured. For this data, to achieve the needed integration of large-scale knowledge discovery techniques with statistical modelling, it is necessary to first uncover descriptive knowledge of complex and heterogeneous objects to make them findable. Then, scalable search structures are needed to efficiently execute similarity access operations, considering also simultaneous execution of multiple queries. Such supporting technologies should serve for semantic data integration and enrichment technologies able to make sense of Big Data for high-level services. We plan to elaborate on these topics and report results, supported by advanced prototype implementations, in respective scientific publication platforms.


Total number of publications: 15

Previous 1 2 Next

You are running an old browser version. We recommend updating your browser to its latest version.

More info