Research interests:
My works are mainly focused in designing languages for data mining (such as the MINE RULE SQL-like operator) and developing data mining systems integrated with the DBMS.
A recent area in which I am involved into is the application of information theory concepts to solve data mining problems, such as the extraction of data dependencies from databases.
Pubblications in Journals:
R.Meo, G.Psaila, S.Ceri, An Extension to SQL for Mining Association Rules in SQL, Data Mining and Knowledge Discovery, vol. 2, num. 2, June 1998, pp. 195-224, Kluwer Academic Publishers.
R. Meo, Theory of Dependence Values, ACM Transactions on
Database Systems, pp. 380-406, vol. 25, num. 3, September 2000.
R.Meo, Maximum Independence and Mutual Information, IEEE Transactions on Information Theory, pp. 318-324, vol.48, n.1, January 2002.
R. Esposito, R.Meo, M. Botta, Answering Constraint-Based Mining Queries on Itemsets Using Previous Materialized Results, Journal of Intelligent Information Systems, pp. 95-111, vol. 26(1), Kluwer, 2006, DOI:10.1007/s10844-006-5453-z. SpringerLink.
A. Gallo, R. Esposito, R.Meo, M. Botta, Incremental Extraction of Association Rules in Applicative Domains, Applied Artificial Intelligence, 21/4, Taylor&Francis, 18pp, April 2007, DOI:10.1080/08839510701252486, web link.
P. Bonfante, F. Cordero, S. Ghignone, D. Ienco, L. Lanfranco, G. Leonardi, R. Meo, S. Montani, L. Roversi, and A. Visconti, A Modular Database Architecture Enabled to Comparative Sequence Analysis, LNCS Transactions on Large-Scale Data- and Knowledge-Centered Systems, Springer LNCS, pp. 124-147, vol. 6990, ISSN: 1869-1994, June 2011.
D. Ienco, R.G.Pensa, R. Meo, From Context to Distance: Learning Dissimilarity for Categorical Data Clustering, ACM Transactions on Knowledge Discovery From Data, Vol. 6, no. 1, p. 1-22, March 2012.
Edited books:
R.Meo, P.Lanzi, M.Klemettinen, Database Support for Data Mining
Applications, Springer-Verlag, LNCS 2682, 2004. SpringerLink.
Preface to the book, commented table of contents and index.
This work was developed during the EU FET project cInQ (IST-2000-26469)
In books:
R.Meo, Using Objectivity/DB in an Application for Configuration Management, in Object Databases in Practice, M.E.S.Loomis, A.B.Chaudhri (eds.), pp. 133-151, Prentice-Hall, 1997.
R.Meo, G.Psaila, XML as a Unifying Framework for Inductive Databases,
in XML Data Management: Native XML and XML-Enabled Database Systems, Akmal B. Chaudhri, Awais Rashid, Roberto Zicari (eds.), ISBN: 0201844524, pp. 401-452, Cap. 15, Addison-Wesley, 2003.
This work has been funded by EU FET project cInQ (IST-2000-26469)
M.Botta, J-F.Boulicaut, C.Masson, R.Meo, Query Languages Supporting
Descriptive Rule Mining: A Comparative Study, in R.Meo, P.Lanzi,
M.Klemettinen, (eds.) Database Support for Data Mining
Applications, Chapter 2, p. 27-54, Springer-Verlag, LNCS 2682, 2004.
This work has been funded by EU FET project cInQ (IST-2000-26469)
R.Meo, G.Psaila, MINE RULE: Semantic Dimensions in Association Rule Mining, in John Wang (ed.), Encyclopedia of Data Warehousing and Mining, ISBN: 1-59140-557-2. Information Science Publishing (an imprint of Idea Group Inc.), 2006.
R.Meo, M.Botta, R. Esposito, A. Gallo, A Novel Incremental Approach to Association Rules Mining in Inductive Databases, in J.-F. Boulicaut, L. de Raedt, H. Mannila (eds.) Constraint-based mining and Inductive Databases. Springer-Verlag LNCS volume 3848. 2006. Springer Link.
R.Meo, P.L. Lanzi, M. Matera, D. Careggio, R. Esposito, Employing Inductive Databases in Concrete Applications, in J.-F. Boulicaut, L. de Raedt, H. Mannila (eds.) Constraint-based mining and Inductive Databases. Springer-Verlag LNCS volume 3848. 2006. Springer Link.
R.Meo, M.Matera, Designing and Mining Web Applications: A Conceptual Modeling Approach, Chapter 8, in Athena Vakali and George Pallis (eds.), Web Data Management Practices: Emerging Techniques and Technologies, Idea Group Inc. ISBN: 1-59904-228-2. 2006.
F. Cordero, S. Ghignone, L. Lanfranco, G. Leonardi, R. Meo, S. Montani, L. Roversi, BIOBITS: A Study on Candidatus Glomeribacter Gigasporarum with a Data Warehouse, Database Technology for Life Sciences and Medicine, Claudia Plant, Christian Böhm (ed.), Chapter 10, pp. 203 - 220. World Scientific Publishing, Singapore, Summer 2011 (pubblication scheduled date). ISBN: 978-981-4307-70-3.
E. Roglia, R.Meo, A SOA-Based System for Territory Monitoring, Chapter in Geospatial Web Services: Advances in Information Interoperability, Peisheng Zhao and Liping Di (eds.), p. 426-454, Idea Group Inc., October 2010. ISBN: 978-1609601928.
E. Roglia, R.Meo, E.Ponassi, Geographical map annotation with significant tags available from social networks, Chapter 17 in XML Data Mining: Models, Methods, and Applications, A.Tagarelli (ed.), p. 425-448, Idea Group Inc., ISBN: 978-1-613-50356-0, November 2011.
R. Meo, L. D'Ambrosi, DepMiner: A method and a system for the extraction of significant dependencies, Chapter 8 in DATA MINING: Foundations and Intelligent Paradigms, D.E. Holmes and L.C. Jain. (Eds.), p. 209-222, Springer Verlag Berlin-Heidelberg, Intelligent System Rerefence Library, vol. 23, ISBN: 978-3-642-23240-4, October 2011.
In conferences:
R.Meo, G.Psaila, S.Ceri, Composite Events in Chimera, Proc. of the 5th International Conference on Extending Database Technology, March 1996, Avignon, France, Springer-Verlag LNCS 1057, pp. 56-76.
R.Meo, G.Psaila, S.Ceri, A New SQL-like Operator for Mining Association Rules, Proc. of the IEEE 22nd International Conference on Very Large Data Bases, pp. 122-133, 3-6 September, 1996, Bombay, India.
E.Baralis, S.Ceri, R.Meo, G.Psaila, M.Richeldi, P.Risimini, AMORE: an Integrated Environment for Database Mining, Atti del Convegno Nazionale Sistemi Evoluti per Basi di Dati, pp.285-302, 25-28 June, 1997, Verona, Italia.
R.Meo, G.Psaila, S.Ceri, A Tightly-Coupled Architecture for Data Mining, Proc. of the IEEE 14th International Conference on Data Engineering, pp. 316-323, February 1998, Orlando, Florida.
E.Baralis, R.Meo, G.Psaila, AMORE: an Integrated Environment for Database Mining, demo session Proc. in 6th International Conference on Extending Database Technology, 23-27 March 1998, Valencia, Spain.
R.Meo, A New Approach for the Discovery of Frequent Itemsets, Proc. of the International Conference on Data Warehouse and Knowledge Discovery, August/September 1999, Firenze, Italia, Springer-Verlag LNCS 1676, pp. 193-202.
E.Baralis, R.Meo, G.Psaila, Data Mining in Data Warehouses, Atti del Settimo Convegno Nazionale Sistemi Evoluti per Basi di Dati, 23-25 giugno 1999, Como, Italia, pp. 51-65.
R.Meo, A new Model for Data Dependencies, Workshop su Apprendimento Automatico e Data Mining, Politecnico di Milano, 12-13 September, 2000. The same paper has been selected for the pubblication on the special number of AIIA Notizie.
M.Botta, J-F.Boulicaut, C.Masson, R.Meo, A comparison between query languages for the extraction of association rules, Proc. of the International Conference on Data Warehouse and Knowledge Discovery, 2-6 September, 2002, Aix-en-Provance, France, Springer-Verlag, LNCS 2454, pp. 1-10.
This work has been funded by EU FET project cInQ (IST-2000-26469)
R.Meo, G.Psaila, Toward XML-Based Knowledge Discovery Systems,
Proc. of the IEEE International Conference on Data Mining, pp. 665-668, 9-12 December, 2002, Maebashi City, Japan.
This work has been funded by EU FET project cInQ (IST-2000-26469)
R.Meo, Optimization of a Language for Data Mining, Proc. of the ACM Symposium on Applied Computing - Data Mining Track, pp. 437-444, 9-12 March, 2003, Melbourne, Florida.
This work has been funded by EU FET project cInQ (IST-2000-26469)
R.Meo, M.Botta, R.Esposito, Query Rewriting in Itemset Mining,
Proc. of the 6th International Conference On Flexible Query Answering
Systems, Springer's Lecture Notes in Artificial Intelligence (LNAI
3055), pp. 111-124, June 24-26 2004, Lyon, France.
This work has been funded by EU FET project cInQ (IST-2000-26469)
R.Meo, P.L.Lanzi, M.Matera, R.Esposito, Integrating Web Conceptual
Modelling and Web Usage Mining, Workshop on Web Mining and Web
Usage Analysis, in conjunction with the 10th ACM SIGKDD International
Conference on Knowledge Discovery and Data Mining (KDD 2004), August 22-25, 2004, Seattle, WA, USA.
This work was developed during the EU FET project cInQ (IST-2000-26469)
Post-Workshop Proceedings have been published by Springer-Verlag in LNCS, Volume 3932, ISBN 978-3-540-47127-1, October, 2006. SpringerLink.
R. Meo, Inductive Databases: Towards a New Generation of Databases for Knowledge Discovery, invited paper at First International Workshop on Integrating Data Mining, Database and Information Retrieval (IDDI), at 16th International Conference on Database and Expert Systems Applications (DEXA), Copenhagen, Denmark, August, 22, 2006. IEEE Computer Society.
A. Gallo, R. Esposito, R. Meo, M. Botta, Optimization of Association Rules Extraction Through Exploitation of Context Dependent Constraints, in Proceedings of 9th Congress of the Italian Association for Artificial Intelligence (AI*IA), LNCS, September, 2006. SpringerLink.
R.Meo, G.Psaila, An XML-Based Database for Knowledge Discovery, in Proceedings of the Second International Workshop on Pattern Representation and Management (PaRMa 2006) in conjunction with the EDBT Conference in Munich, Germany, on March 30, 2006.
An extended version of this paper has been published by Springer-Verlag, in the Post-Workshop Proceedings, LNCS volume 4254/2006 entitled Current Trends in Database Technology, T. Grust et. al. (eds), ISBN 978-3-540-46788-5, SpringerLink.
A.Gallo, R.Meo, Using a Reinforced Concept Lattice to Incrementally Mine Association Rules from Closed Itemsets, in Post-Workshop Proceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases (KDID 2006) in conjunction with the ECML/PKDD Conference in Berlin, Germany, September 18, 2006.
Published by Springer-Verlag, LNCS Volume 4747, ISBN 978-3-540-75548-7, September 2007. SpringerLink.
D.Ienco, R.Meo, Exploration and Reduction of the Feature Space by Hierarchical Clustering, in Proceedings of the 2008 SIAM International Conference on Data Mining (SDM08) in Atlanta, Georgia, USA, April, 24-26, 2008. ISBN: 978-0-89871-654-2. On-line SIAM Data Mining Proceedings.
E.Roglia, R.Cancelliere, R.Meo, Classification of Chestnuts with Feature Selection by Noise Resilient Classifiers, in Proceedings of the 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning (ESANN08) Bruges (Belgium), 23-25 April, 2008.
D.Ienco, R.Meo, M.Botta, Using PageRank in Feature Selection, in Proceedings of the 16th Italian Symposium on Advanced Database Systems (SEBD08), Mondello (Palermo), Italy, 22-25 June, 2008.
D.Ienco, R.Meo, Clustering the Feature Space, in Proceedings of the 16th Italian Symposium on Advanced Database Systems (SEBD08), Mondello (Palermo), Italy, 22-25 June, 2008.
D.Ienco, R.Meo, Towards Automatic Construction of Conceptual Taxonomies, in Proceedings of the 10th International Conference on Data Warehousing and Knowledge Discovery (DaWak08), Torino, Italy, 1-5 September, 2008.
E.Roglia, R.Meo, A Composite Wrapper for Feature Selection, in Proceedings of Workshop on Data Mining and Bioinformatics in AI*IA - Intelligenza Artificiale e Scienza della Vita (DMBIO08) Cagliari (Italy), 13 September, 2008.
D.Ienco, R.Meo, M.Botta, Using PageRank in Feature Selection, in Proceedings of the 16th Italian Symposium on Advanced Database Systems (SEBD08), Mondello (Palermo), Italy, 22-25 June, 2008.
D.Bachar, R.Meo, A Novel Distance-Based Classifier Built on Pattern Ranking, in Proceedings of 24th ACM Symposium on Applied Computing (SAC 2009), Data Mining Track, Honolulu, Hawaii, 8-12 March, 2009.
D.Ienco, R.Meo, Distance based Clustering for Categorical Data, in Proceedings of the 17th Italian Symposium on Advanced Database Systems (SEBD09), Camogli (Genova), Italy, 21-24 June, 2009.
D.Ienco, R.G.Pensa, R.Meo, Parameter-free Hierarchical Co-Clustering by n-Ary Splits, in Proceedings of 24th ECML/PKDD (ECML/PKDD 2009), Part I, LNAI 5781, pp. 580-595, Bled, Slovenia, 7-11 September, 2009.
D.Ienco, R.G.Pensa, R.Meo, Context-based Distance Learning for Categorical Data Clustering, in Proceedings of 8th International Symposium on
Intelligent Data Analysis (IDA 2009), LNCS 5772-0083, pp. 83-94, Lyon, France, 31 August-2 September, 2009.
R.Meo, L.D'Ambrosi, Finding High Order Dependencies in Data, in Proceedings of 26th International Symposium on Computer and Information Sciences (ISCIS 2011), LNEE, Springer-Verlag London, ISBN: 978-1-4471-2154-1, DOI: 10.1007/978-1-4471-2155-8_4, pp. 35-41, The Royal Society London, UK, 26-28 September, 2011. SpringerLink.
R.Meo, E.Roglia, E.Ponassi, MetaData Retrieval: A Software Prototype for the Annotation of Maps with Social Metadata, in Proceedings of 26th ECML/PKDD (ECML/PKDD 2011), LNCS vol. 6913, pp. 642-645, Athens, Greece, 5-9 September, 2011.
R.Meo, E.Roglia, E.Ponassi, MetaData Retrieval: Annotation of Geo-Referenced Maps with Social Metadata in Support to Unmanned Aircraft Vehicles Missions, in Proceedings of 2011 NASA Conference on Intelligent Data Understanding (CIDU 2011), extended abstract, pp.2, Moutain View, CA, 19-21 October, 2011.
Technical Reports:
M.Botta, R.Meo, M.L.Sapino, Incremental Execution of the MINE RULE Operator, Rapporto Tecnico RT66-2002, Dipartimento di Informatica, Università di Torino, May, 2002.
R.Meo, Replacing Support in Association Rule Mining, Rapporto Tecnico RT70-2003, Dipartimento di Informatica, Università di Torino, April, 2003.
M.Botta, R.Meo, C.Malangone, Association Rules Extraction with MINE RULE Operator, Rapporto Tecnico RT73-2003, Dipartimento di Informatica, Università di Torino, April, 2003.
R.Meo, D.Careggio, Employing Inductive Databases in Financial Data, Rapporto Tecnico RT76-2003, Dipartimento di Informatica, Università di Torino, December, 2003.
M.Botta, R.Esposito, A.Gallo, R.Meo, Optimizing
Inductive Queries in Frequent Itemset Mining, Rapporto Tecnico RT79-2004, Dipartimento di Informatica, Università di Torino, May, 2004.
D.Bachar, R.Meo. A distance-based classifier built on class model, Rapporto Tecnico RT112-2008, Dipartimento di Informatica, Università di Torino, October, 2008.
Giuseppe Rizzo, Rosa Meo, Ruggero G. Pensa, Giacomo Falcone,
Raphaël Troncy Shaping City Neighborhoods Leveraging on Crowd Sensors, Rapporto Tecnico RT153-15, Dipartimento di Informatica, Università di Torino, July, 2015.
Didactic Pubblications:
A.R.Meo, M.Mezzalama, F.Peiretti, R.Meo, Fondamenti di Informatica I, ed. UTET, Torino, 1996.
M.Meo, R.Meo, M.Mezzalama, Esercizi di Fondamenti di Informatica, ed. Pitagora, Bologna, 1996.
Last updated version: June, 18th, 2004
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