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Luca Pappalardo

Researcher at Istituto di Scienza e Tecnologie dell'Informazione

Publications -  104
Citations -  2741

Luca Pappalardo is an academic researcher from Istituto di Scienza e Tecnologie dell'Informazione. The author has contributed to research in topics: Computer science & Mobility model. The author has an hindex of 24, co-authored 87 publications receiving 1894 citations. Previous affiliations of Luca Pappalardo include National Research Council & University of Pisa.

Papers
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Journal ArticleDOI

Returners and explorers dichotomy in human mobility

Luca Pappalardo, +6 more
- 08 Sep 2015 - 
TL;DR: It is shown that returners and explorers play a distinct quantifiable role in spreading phenomena and that a correlation exists between their mobility patterns and social interactions.
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Effective injury forecasting in soccer with GPS training data and machine learning.

Alessio Rossi, +6 more
- 25 Jul 2018 - 
TL;DR: This paper proposes a multi-dimensional approach to injury forecasting in professional soccer that is based on GPS measurements and machine learning, and constructs an injury forecaster that is both accurate and interpretable by providing a set of case studies of interest to soccer practitioners.
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A public data set of spatio-temporal match events in soccer competitions.

Luca Pappalardo, +6 more
- 28 Oct 2019 - 
TL;DR: The nature of team sports like soccer, halfway between the abstraction of a game and the reality of complex social systems, combined with the unique size and composition of this dataset, provide the ideal ground for tackling a wide range of data science problems.
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Tiles: an online algorithm for community discovery in dynamic social networks

Giulio Rossetti, +3 more
- 01 Aug 2017 - 
TL;DR: This work proposes Tiles, an algorithm that extracts overlapping communities and tracks their evolution in time following an online iterative procedure, and compares it with state-of-the-art community detection algorithms on both synthetic and real world networks having annotated community structure.
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Understanding the patterns of car travel

Luca Pappalardo, +6 more
- 29 Jan 2013 - 
TL;DR: Based on a unique dataset consisting of the GPS trajectories of 10 million travels accomplished by 150,000 cars in Italy, it is found how to build an extremely accurate model that estimates the real traffic values as measured by road sensors.