The special issue of the Journal of Intelligent Information Systems (JIIS) features papers from the first International Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2011), which was held in Bristol UK, on September 24th 2012 in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2012). The first paper, 'Link Classification with Probabilistic Graphs', by Nicola Di Mauro, Claudio Taranto and Floriana Esposito, proposes two machine learning techniques for the link classification problem in relational data exploiting the probabilistic graph representation. The second paper, 'Hierarchical Object-Driven Action Rules', by Ayman Hajja, Zbigniew W. Ras, and Alicja A. Wieczorkowska, proposes a hybrid action rule extraction approach that combines key elements from both the classical action rule mining approach, and the object-driven action rule extraction approach to discover action rules from object-driven information systems.

Mining complex patterns

Masciari Elio;Manco Giuseppe
2014

Abstract

The special issue of the Journal of Intelligent Information Systems (JIIS) features papers from the first International Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2011), which was held in Bristol UK, on September 24th 2012 in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2012). The first paper, 'Link Classification with Probabilistic Graphs', by Nicola Di Mauro, Claudio Taranto and Floriana Esposito, proposes two machine learning techniques for the link classification problem in relational data exploiting the probabilistic graph representation. The second paper, 'Hierarchical Object-Driven Action Rules', by Ayman Hajja, Zbigniew W. Ras, and Alicja A. Wieczorkowska, proposes a hybrid action rule extraction approach that combines key elements from both the classical action rule mining approach, and the object-driven action rule extraction approach to discover action rules from object-driven information systems.
2014
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Mining Complex Patterns
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/261121
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