Probabilistic Graphical Models for Scalable Data Analysis
Published on Jan 01, 2016 | By andres r. masegosa | Permalink
The main objective of this project is to generate a set of methodological developments in the PGMs areas and scalable data analysis, sufficiently grounded and innovative to be incorporated into the gallery of tools for massive data processing. One of these contexts is the analysis of documentary collections and their subsequent use by users to resolve information needs effectively and efficiently. Currently, these textual sources are usually large but they are also growing continuously, making their treatment and analysis in a scalable way a real challenge. In a complementary way, the project intends to produce the necessary software tools for the application of these methodological developments to real problems. In this way, the purpose of this project is twofold: generating new knowledge of high scientific quality within the field of scalable data analytics and allowing technology transfer using the software produced.