Propelled by a fast evolving landscape of techniques and datasets, data science is growing rapidly. Against this background, topological data analysis (TDA) has carved itself a niche for the analysis of datasets that present complex interactions and rich structures. Its distinctive feature, topology, allows TDA to detect, quantify and compare the mesoscopic structures of data, while also providing a language able to encode interactions beyond networks. Here we briefly present the TDA paradigm and some applications, in order to highlight its relevance to the data science community.

Topological analysis of data / Patania, Alice; Vaccarino, Francesco; Petri, Giovanni. - In: EPJ DATA SCIENCE. - ISSN 2193-1127. - ELETTRONICO. - (2017). [10.1140/epjds/s13688-017-0104-x]

Topological analysis of data

PATANIA, ALICE;VACCARINO, FRANCESCO;
2017

Abstract

Propelled by a fast evolving landscape of techniques and datasets, data science is growing rapidly. Against this background, topological data analysis (TDA) has carved itself a niche for the analysis of datasets that present complex interactions and rich structures. Its distinctive feature, topology, allows TDA to detect, quantify and compare the mesoscopic structures of data, while also providing a language able to encode interactions beyond networks. Here we briefly present the TDA paradigm and some applications, in order to highlight its relevance to the data science community.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2674779
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