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Project

Computational models for big data algorithms.

A central theme in computer science is the design of efficient algorithms. However, recent experiments show that many standard algorithms degrade significantly in the presence of big data. This is particularly true when evaluating classes of queries in the context of databases. Unfortunately, existing theoretical tools for analyzing algorithms cannot tell whether or not an algorithm will be feasible on big data. Indeed, algorithms that are considered to be tractable in the classical sense are not tractable anymore when big data is concerned. This calls for a revisit of classical complexity theoretical notions. The development of a formal foundation and an accompanying computational complexity to study tractability in the context of big data is the main goal of this project.
Date:1 Mar 2014 →  31 Jul 2015
Keywords:THEORY OF DATABASES, COMPLEXITY
Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences