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.


Tutti gli autori

  • 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

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Codici ASJC

Non Disponibile