Assistant Professor

Dipartimento di Informatica
Università degli Studi di Bari
Via Orabona, 4
70126 Bari - Italy

phone: +39 080 5442276
fax: +39 080 5443196
email: lisi@di.uniba.it

Topics of my publications

Application to Spatial Data Mining
Application to Document Analysis and Understanding

Inductive Logic Programming

• F.A. Lisi & D. Malerba (2003). Inducing Multi-Level Association Rules from Multiple Relations. Machine Learning (accepted for publication).

• F.A. Lisi & D. Malerba (2003). Ideal Refinement of Descriptions in AL-log. In T. Horvath and A. Yamamoto (Eds.), Inductive Logic Programming, Series: Lecture Notes in Artificial Intelligence, Vol. 2835, 215-232, Springer: Berlin.

• F.A. Lisi & D. Malerba (2003). Bridging the Gap between Horn Clausal Logic and Description Logics in Inductive Learning. In A. Cappelli and F. Turini (Eds.), AI*IA 2003: Advances in Artificial Intelligence, Series: Lecture Notes in Artificial Intelligence, Vol. 2829, 53-64, Springer: Berlin.

• F.A. Lisi (2003). Data Mining in Hybrid Languages via ILP. In D. Calvanese, G. De Giacomo and E. Franconi (Eds.), Proc. 2003 International Workshop on Description Logics (DL'03).

• F.A. Lisi & D. Malerba (2003). Towards Object-Relational Data Mining. In S. Flesca, S. Greco, D. Saccà & E. Zumpano (Eds.), Atti dell'Undicesimo Convegno Nazionale su Sistemi Evoluti per Basi di Dati, 269-280, Rubbettino Editore, Italy.

 
• F.A. Lisi, S. Ferilli & N. Fanizzi (2002). Object Identity as Search Bias for Pattern Spaces. In F. van Harmelen (ed.): ECAI 2002. Proceedings of the 15th European Conference on Artificial Intelligence, 375-379, IOS Press, Amsterdam.

• F.A. Lisi & D. Malerba (2002). Efficient Discovery of Multiple-level Patterns. In P. Ciaccia, F. Rabitti & G. Soda (Eds.), Atti del Decimo Convegno Nazionale su Sistemi Evoluti per Basi di Dati, 237-250, Centro Stampa 2P, Pontassieve, Italy.

• D. Malerba & F.A. Lisi (2001). An ILP Method for Spatial Association Rule Mining. In A. Knobbe and D. van der Wallen (Eds.), Notes of the ECML/PKDD 2001 Workshop on Multi-Relational Data Mining, 18-29, Freiburg, Germany.

• F. Esposito, D. Malerba, & F. A. Lisi (2000). Induction of Recursive Theories in the Normal ILP Setting: Issues and Solutions. In J. Cussens and A. Frisch (Eds.), Inductive Logic Programming, LNAI 1866, 93-111, Springer-Verlag: Berlin.

• D. Malerba, F. Esposito, & F.A. Lisi (1998). Learning recursive theories with ATRE. In H. Prade (Ed.), Proc. of the 13^th European Conference on Artificial Intelligence, 435-439, John Wiley & Sons, Chichester, England.

Application to Spatial Data Mining

• A. Appice, M. Ceci, A. Lanza, F.A. Lisi & D. Malerba (2003). Discovery of Spatial Association Rules in Georeferenced Census Data: A Relational Mining Approach. Intelligent Data Analysis, 7 (in press).

• D. Malerba, F.A. Lisi, A. Appice & F. Sblendorio (2003). Mining Census and Geographic Data in Urban Planning Environments. In L. Santini & D. Zotta (Eds.), Atti della Terza Conferenza Nazionale su Informatica e Pianificazione Urbana e Territoriale (INPUT 2003), Alinea Editrice, Firenze, Italy.

• A. Appice, F.A. Lisi, D. Malerba & F. Sblendorio (2003). Analysing Geo-referenced Census Data: a Case Study. Presented at the Convegno Scientifico Intermedio della Società Italiana di Statistica, Napoli, Italy, 9-11 June.

• D. Malerba, F. Esposito, A. Lanza, F.A. Lisi & A. Appice (2003). Empowering a GIS with Inductive Learning Capabilities: The case of INGENS. Computers, Environment and Urban Systems, 27: 265 –281, Elsevier Science.

• D. Malerba, F. Esposito, F.A. Lisi & A. Appice (2002). Mining Spatial Association Rules in Census Data. Research in Official Statistics, 5(1): 21-44.

• F.A. Lisi & D. Malerba (2002). SPADA: A Spatial Association Discovery System. In A. Zanasi, C.A. Brebbia, N.F.F. Ebecken and P. Melli (Eds.), Data Mining III, Series: Management Information Systems, Vol. 6, 157-166, WIT Press.

• A. Lanza, D. Malerba, F.A. Lisi, A. Appice & M. Ceci (2002). Generating Logic Descriptions for the Automated Interpretation of Topographic Maps. In D. Blostein and Y.-B. Kwon (Eds.), Graphics Recognition: Algorithms and Applications, Series: Lecture Notes in Computer Science, Vol. 2390, 193-203, Springer: Berlin.

• D. Malerba, F.A. Lisi, A. Appice & F. Sblendorio (2002). Mining Spatial Association Rules in Census Data: A Relational Approach. In P. Brito and D. Malerba (Eds.), Notes of the ECML/PKDD 2002 Workshop on Mining Official Data, 80-93, Helsinki University Printing House: Helsinki, ISBN: 952-10-0637-4.

• D. Malerba, F. Esposito, A. Lanza & F.A. Lisi (2001). Machine Learning for Information Extraction from Topographic Maps. Chapter 12 in H. Miller & J. Han (Eds.), Geographic Data Mining and Knowledge Discovery, Taylor & Francis.

• D. Malerba & F.A. Lisi (2001). Discovering Associations between Spatial Objects: An ILP Application. In C. Rouveirol and M. Sebag (Eds.), Inductive Logic Programming, LNAI 2157, 156-163, Springer-Verlag: Berlin.

• D. Malerba, F. Esposito, A. Lanza & F.A. Lisi (2001). Automated Interpretation of Topographic Maps: Beyond Symbol Recognition. Proc. 4th IAPR Int. Workshop on Graphics Recognition, 288-297, Kingston, Ontario, Canada.

• D. Malerba, F. Esposito, A. Lanza & F.A. Lisi (2001). First-order Rule Induction for the Recognition of Morphological Patterns in Topographic Maps. In P. Perner (ed.), Machine Learning and Data Mining in Pattern Recognition, LNAI 2123, 88-101, Springer: Berlin.

• D. Malerba, F. Esposito, A. Lanza & F.A. Lisi (2001). Geo-Spatial Knowledge Discovery for Map Interpretation. In A. Belward, E. Binaghi, P.A. Brivio, G.A. Lanzarone & G. Tosi (Eds.), Proc. Int. Workshop on Geo-Spatial Knowledge Processing for Natural Resource Management, 112-116, Artestampa, Daverio (Varese), Italy.

• D. Malerba, F. Esposito, & F.A. Lisi (2001). Mining Association Rules in Spatial Databases: A Logic-based Computational Method. In A. Celentano, L. Tanca & P.Tiberio (Eds.), Atti del Nono Convegno Nazionale su Sistemi Evoluti per Basi di Dati, 223-237, LCM Selecta Group, Milano, Italy.

• F. Esposito, A. Lanza, F.A. Lisi, D. Malerba & V. Marengo (2001). Knowledge Discovery Technologies for Urban Spatial Planning. In G. Concilio & V. Monno (Eds.), Proc. 2nd National Conference on Information Technology and Spatial Planning, Dedalo Edizioni, Bari, Italy.

• D. Malerba, F. Esposito & F.A. Lisi (2001). Mining Spatial Association Rules in Census Data. In Proc. 4th Int. Seminar on New Techniques and Technologies for Statistics (NTTS 2001), Crete, June 18-22, 2001.

• D. Malerba, F. Esposito, & F.A. Lisi (2001). A Logical Framework for Frequent Pattern Discovery in Spatial Data. In I. Russell & J. Kolen (Eds.), Proc. of the 14th Int. FLAIRS Conference, Special track on Spatiotemporal Reasoning, 557-561, AAAI Press, Menlo Park, California.

• D. Malerba, F. Esposito, & F.A. Lisi (2000). An ILP Approach to the Discovery of Spatial Association Rules. AI*IA Notizie, vol. XIII(4), 57-62.

• D. Malerba, F. Esposito, A. Lanza, & F. A. Lisi (2000). Discovering geographic knowledge: The INGENS system. In Z.W. Ras and S. Ohsuga (Eds.), Foundations of Intelligent Systems, LNAI 1932, 40-48, Springer: Berlin.

• D. Malerba, F. Esposito, & F.A. Lisi (2000). Mining Spatial Association Rules. In Atti della Giornata di Studio del Gruppo di Lavoro AI*IA su Apprendimento Automatico "Apprendimento Automatico e Data Mining: Metodologie, Strumenti ed Applicazioni", Milano, Italy, September 12.

• D. Malerba, F. Esposito, A. Lanza, F. A. Lisi & L. Sanarico (2000). INGENS: A Geographical Information System with Inductive Learning Capabilities. In Proc. Int. Workshop on Emerging Technologies for Geo-based Applications, Ascona, Switzerland, 249-263.

Application to Document Analysis and Understanding

• D. Malerba, F. Esposito, F.A. Lisi, & O. Altamura (2001). Automated Discovery of Dependencies Between Logical Components in Document Image Understanding. In B. Werner (Ed.), Proc. 6th Int. Conference on Document Analysis and Recognition, 174-178, IEEE Computer Society, Los Alamitos, California.

• F. Esposito, D. Malerba, & F.A. Lisi (2001). Multiple Predicate Learning for Document Image Understanding. In I. Russell & J. Kolen (Eds.), Proc. of the 14th Int. FLAIRS Conference, Special track on Machine Learning, 372-376, AAAI Press, Menlo Park, California.

• F. Esposito, D. Malerba, & F. A. Lisi (2000). Understanding Multi-Page Documents: A Multiple Concepts Learning Problem. In F. Esposito and D. Malerba (Eds.), Notes of the ECAI2000-Workshop on Machine Learning in Computer Vision, Berlin, Germany, 31-38.

• F. Esposito, D. Malerba, & F.A. Lisi (2000). Machine Learning for Intelligent Processing of Printed Documents. In Z. Ras and A. Skowron (Eds.), Journal of Intelligent Information Systems 16, Special Issue on Methodologies for Intelligent Information Systems, Kluwer Academic Publishers, 175-198.

• F.A. Lisi, D. Malerba, & F. Esposito (1999). Apprendimento automatico di modelli visuali da immagini di documento, Atti del Workshop AI*IA su Apprendimento e Percezione nei Sistemi Robotici, Parma.

• O. Altamura, F. Esposito, F. A. Lisi, & D. Malerba (1999). Symbolic Learning Techniques in Paper Document Processing. In P. Perner and M. Petrou (Eds.), Machine Learning and Data Mining in Pattern Recognition, LNAI 1715, 159-173, Springer: Berlin.

• O. Altamura, F. Esposito, F. A. Lisi, & D. Malerba (1999). Attributional and Relational Learning Issues in Document Analysis and Recognition, Proc. of the ICML '99 Workshop on Machine Learning in Computer Vision, 20-31, Bled, Slovenia.

• F. Esposito, D. Malerba, & F.A. Lisi (1999). Machine Learning for Intelligent Document Processing: The WISDOM System. In Z.W. Ras and A. Skowron (Eds.), Foundations of Intelligent Systems, LNAI 1609, 103-113, Springer: Berlin.

• F. Esposito, D. Malerba, G. Semeraro, & F.A. Lisi (1998). Machine learning issues in analysis, classification and understanding of document images. Workshop on Learning in Computer Vision.

Intelligent Interfaces

• B. De Carolis & F.A. Lisi (2002). A NLG-based Presentation Method for Supporting KDD End-Users. In M.-S. Hacid, Z. Ras, D.A. Zighed & Y. Kodratoff (Eds.), Foundations of Intelligent Systems, LNAI 2366, 535-543, Springer: Berlin.

• P. Buono, F.M. Costabile & F.A. Lisi (2001). Supporting Data Analysis through Visualizations. In S.J. Simoff, M. Noirhomme-Fraiture and M.H. Böhlen (Eds.), Notes of the ECML/PKDD 2001 Workshop on Visual Data Mining, 67-78, Freiburg, Germany.

• B. De Carolis & F.A. Lisi (2001). A Multimodal Interface for supporting Urban and Land Planning. In G. Concilio & V. Monno (Eds.), Proc. 2nd National Conference on Information Technology and Spatial Planning, Dedalo Edizioni, Bari, Italy.

Symbolic Data Analysis

• F. Esposito, D. Malerba, & F. A. Lisi (2000). Matching Symbolic Objects. Chapter 8.4 in H. H. Bock & E. Diday (Eds.), Analysis of Symbolic Data. Exploratory methods for extracting statistical information from complex data, Series: Studies in Classification, Data Analysis, and Knowledge Organization, vol. 15, Springer-Verlag: Berlin, 186-197.

• F. Esposito, D. Malerba, & F.A. Lisi (1998). Flexible Matching of Boolean Symbolic Objects. Proc. 3rd Int. Seminar on New Techniques & Technologies for Statistics (NTTS'98), 157-162.