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2008
R. Ortale, Ritacco, E., Pelekisy, N., Trasarti, R., Costa, G., Giannotti, F., Manco, G., Renso, C., and Theodoridis, Y., “DAEDALUS: A knowledge discovery analysis framework for movement data”, in SEBD, 2008, pp. 191-198.
R. Ortale, Ritacco, E., Pelekis, N., Trasarti, R., Costa, G., Giannotti, F., Manco, G., Renso, C., and Theodoridis, Y., “The DAEDALUS framework: progressive querying and mining of movement data”, in GIS, 2008, p. 52.
G. Manco, Baglioni, M., Giannotti, F., Kuijpers, B., Raffaetà, A., and Renso, C., “Querying and Reasoning for Spatiotemporal Data Mining”, in Mobility, Data Mining and Privacy, 2008, pp. 335-374.
G. Manco, Baglioni, M., Giannotti, F., Kuijpers, B., Raffaetà, A., and Renso, C., “Querying and Reasoning for Spatio-Temporal Data Mining”, Mobility, Privacy, and Geography: a Knowledge Discovery vision, 2008.
2004
F. Giannotti, Manco, G., and Turini, F., “Specifying Mining Algorithms with Iterative User-Defined Aggregates”, IEEE Trans. Knowl. Data Eng., vol. 16, pp. 1232-1246, 2004.
F. Giannotti, Manco, G., and Turini, F., “Towards a Logic Query Language for Data Mining”, in Database Support for Data Mining Applications, 2004, pp. 76-94.
2003
F. Giannotti, Manco, G., and Wijsen, J., “Logical Languages for Data Mining”, in Logics for Emerging Applications of Databases, 2003, pp. 325-361.
2002
F. Giannotti, Gozzi, C., and Manco, G., “Characterizing Web User Accesses: A Transactional Approach to Web Log Clustering”, in ITCC, 2002, p. 312.
F. Giannotti, Gozzi, C., and Manco, G., “Clustering Transactional Data”, in PKDD, 2002, pp. 175-187.
F. Giannotti and Manco, G., “LDL-M$_{\mbox{ine}}$: Integrating Data Mining with Intelligent Query Answering”, in JELIA, 2002, pp. 517-520.
2001
F. Giannotti, Gozzi, C., and Manco, G., “Clustering Transactional Data”, in SEBD, 2001, pp. 163-176.
F. Bonchi, Giannotti, F., Manco, G., Renso, C., Nanni, M., Pedreschi, D., and Ruggieri, S., “Data Mining for Intelligent Web Caching”, in ITCC, 2001, pp. 599-603.
F. Bonchi, Giannotti, F., Manco, G., Renso, C., Nanni, M., Pedreschi, D., and Ruggieri, S., “Data Mining for Intelligent Web Caching”, in ITCC, 2001, pp. 599-603.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., “Nondeterministic, Nonmonotonic Logic Databases”, IEEE Trans. Knowl. Data Eng., vol. 13, pp. 813-823, 2001.
F. Giannotti, Manco, G., and Turini, F., “Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study”, in PKDD, 2001, pp. 128-139.
F. Bonchi, Giannotti, F., Gozzi, C., Manco, G., Nanni, M., Pedreschi, D., Renso, C., and Ruggieri, S., “Web log data warehousing and mining for intelligent web caching”, Data Knowl. Eng., vol. 39, pp. 165-189, 2001.
F. Bonchi, Giannotti, F., Gozzi, C., Manco, G., Nanni, M., Pedreschi, D., Renso, C., and Ruggieri, S., “Web log data warehousing and mining for intelligent web caching”, Data Knowl. Eng., vol. 39, pp. 165-189, 2001.
F. Bonchi, Giannotti, F., Gozzi, C., Manco, G., Nanni, M., Pedreschi, D., Renso, C., and Ruggieri, S., “Web Log Data Warehousing and Mining for Intelligent Web Caching”, Data and Knowledge Engineering, 2001.
2000
F. Giannotti and Manco, G., “Declarative Knowledge Extraction with Interactive User-Defined Aggregates”, in FQAS, 2000, pp. 435-444.
F. Giannotti and Manco, G., “Making Knowledge Extraction and Reasoning Closer”, in PAKDD, 2000, pp. 360-371.
1999
F. Giannotti, Manco, G., Pedreschi, D., and Turini, F., “Experiences with a Logic-based knowledge discovery Support Environment”, in 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 1999.
F. Giannotti, Manco, G., Pedreschi, D., and Turini, F., “Experiences with a Logic-Based Knowledge Discovery Support Environment”, in AI*IA, 1999, pp. 202-213.
F. Giannotti, Manco, G., Nanni, M., Pedreschi, D., and Turini, F., “Integration of Deduction and Induction for Mining Supermarket Sales Data”, in SEBD, 1999, pp. 117-131.
F. Giannotti and Manco, G., “Querying inductive Databases via Logic-Based user-defined aggregates”, in APPIA-GULP-PRODE, 1999, pp. 605-620.
F. Giannotti and Manco, G., “Querying Inductive Databases via Logic-Based User-Defined Aggregates”, in PKDD, 1999, pp. 125-135.

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