"Want to come play with me?" Outlier subgroup discovery on spatio-temporal interactions

• Tipo: Artigo em Revista Científica Internacional
• Data: 2021

Autores

Carolina Centeio Jorge (Autor) Outra; Martin Atzmueller (Autor) Outra; Behzad M. Heravi (Autor) Outra; Jenny L. Gibson (Autor) Outra; Rosaldo J. F. Rossetti (Autor) FEUP; Cláudio Rebelo de Sá (Autor) Outra

Revista

Título: Expert Systems

Vol. 40 Nº 5

Páginas: 1-20

ISSN: 0266-4720

Editora: Wiley-Blackwell

Indexação

ISI Web of Knowledge - 0 Citações

ISI Web of Science

Scopus - 1 Citação

Classificação Científica

FOS: Ciências exactas e naturais > Matemática

CORDIS: Ciências Físicas > Ciência de computadores

Outras Informações

ID Authenticus: P-00T-MFT

DOI: 10.1111/exsy.12686

Abstract (EN): Our lives are made of social interactions which can be recorded through personal gadgets as well as sensors capturing ubiquitous and social data. This type of data, such as spatio-temporal data from the real-time location of people, for example, can then be used for inferring interactions which can be translated into behavioural patterns. In this paper, we consider the automatic discovery of exceptional social behaviour from spatio-temporal interaction data, focusing on two areas: exceptional subgroups and spatio-temporal outliers - both in the form of descriptive patterns. For that, we propose a method for exceptional social behaviour discovery, combining subgroup discovery and network science methods for identifying behaviour that deviates from the norm. We also propose the use of two outlier detection metrics for identifying outliers, namely the Local Outlier Factor (LOF) and the Voronoi area. We applied the proposed method on synthetic data as well as two real datasets containing location data from children playing in the school playground. Our results indicate that this is a valid approach which is able to obtain meaningful knowledge from the data.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 20