Approximation and Randomised String Processing – PARSe
In this project we aim to study the foundations of processing large-scale, noisy string data. Our goal is to understand the limit of computations, and to provide new ultra-efficient algorithms and data structures for processing such data, inspired by approaches in hashing and high-dimensional geometry. We will focus on three research directions: streaming pattern matching, probabilistic text indexing, and sketching-based sting comparison. Algorithms and data structures on strings have traditionally been exploited in such fields as Bioinformatics, Information Retrieval, and Digital Security, and we expect our project to have a significant impact on these fields.
Project coordination
Tatiana Starikovskaya (Département d'Informatique de l'Ecole Normale Supérieure)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
University of Wroclaw / Institute of Informatics
DI ENS Département d'Informatique de l'Ecole Normale Supérieure
IRISA Institut de Recherche en Informatique et Systèmes Aléatoires
LIRMM Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier
Help of the ANR 202,340 euros
Beginning and duration of the scientific project:
December 2020
- 48 Months
