Relational learning of disjunctive patterns in spatial networks
Abstract
In spatial domains, objects present high heterogeneity and are connected by several relationships to form complex networks. Mining spatial networks can provide information on both the objects and their interactions. In this work we propose a descriptive data mining approach to discover relational disjunctive patterns in spatial networks. Relational disjunctive patterns permit to represent spatial relationships that occur simultaneously with or alternatively to other relationships. Pruning of the search space is based on the anti-monotonicity property of support. The application to the problem of urban accessibility proves the viability of the proposal.
Autore Pugliese
Tutti gli autori
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LOGLISCI C.;MALERBA D.
Titolo volume/Rivista
Non Disponibile
Anno di pubblicazione
2010
ISSN
1613-0073
ISBN
Non Disponibile
Numero di citazioni Wos
Nessuna citazione
Ultimo Aggiornamento Citazioni
Non Disponibile
Numero di citazioni Scopus
1
Ultimo Aggiornamento Citazioni
Non Disponibile
Settori ERC
Non Disponibile
Codici ASJC
Non Disponibile
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