Travelled to:1 × Brazil
1 × Canada
1 × Italy
1 × Korea
1 × Switzerland
1 × USA
1 × United Kingdom
4 × Germany
Collaborated with:D.Malerba A.Appice M.Berardi O.Altamura F.Esposito C.Loglisci L.Macchia G.Porcelli N.Barile S.Rawles P.A.Flach H.L.Viktor E.Paquet H.Guo C.Caruso F.Fumarola C.Valente I.Frommholz H.Brocks U.Thiel E.J.Neuhold L.Iannone G.Semeraro
Talks about:relat (5) learn (5) data (5) document (4) approach (4) mine (4) transduct (3) layout (3) regress (2) correct (2)
Person: Michelangelo Ceci
DBLP: Ceci:Michelangelo
Contributed to:
2012
20102009
200720072005
2004
2003
2003200320032003Wrote 15 papers:
- MLDM-2012-CeciAVMPG #classification #paradigm #relational
- Transductive Relational Classification in the Co-training Paradigm (MC, AA, HLV, DM, EP, HG), pp. 11–25.
- MLDM-2012-MacchiaCM #mining #modelling #network #ranking
- Mining Ranking Models from Dynamic Network Data (LM, MC, DM), pp. 566–577.
- SAC-2010-AppiceCM #learning
- Transductive learning for spatial regression with co-training (AA, MC, DM), pp. 1065–1070.
- SAC-2010-CeciALM #approach #data mining #mining #ranking #relational
- Complex objects ranking: a relational data mining approach (MC, AA, CL, DM), pp. 1071–1077.
- MLDM-2009-CeciALCFVM #data type #detection #mining #relational
- Relational Frequent Patterns Mining for Novelty Detection from Data Streams (MC, AA, CL, CC, FF, CV, DM), pp. 427–439.
- ICDAR-2007-CeciBPM #approach #data mining #detection #mining #order
- A Data Mining Approach to Reading Order Detection (MC, MB, GP, DM), pp. 924–928.
- MLDM-2007-CeciABM #learning #relational
- Transductive Learning from Relational Data (MC, AA, NB, DM), pp. 324–338.
- ICDAR-2005-BerardiACM #analysis #layout #process
- A color-based layout analysis to process censorship cards of film archives (MB, OA, MC, DM), pp. 1110–1114.
- ICDAR-2005-CeciBM #comprehension #documentation #image #learning #logic #relational #statistics
- Relational Learning techniques for Document Image Understanding: Comparing Statistical and Logical approaches (MC, MB, DM), pp. 473–477.
- ICML-2004-AppiceCRF #multi #problem
- Redundant feature elimination for multi-class problems (AA, MC, SR, PAF).
- ECDL-2003-FrommholzBTNISBC #collaboration
- Document-Centered Collaboration for Scholars in the Humanities — The COLLATE System (IF, HB, UT, EJN, LI, GS, MB, MC), pp. 434–445.
- ECIR-2003-CeciM #classification #documentation #html
- Hierarchical Classification of HTML Documents with WebClassII (MC, DM), pp. 57–72.
- ICDAR-2003-MalerbaEACB #approach #documentation #layout #machine learning
- Correcting the Document Layout: A Machine Learning Approach (DM, FE, OA, MC, MB), p. 97–?.
- ICML-2003-BerardiCEM #analysis #layout #learning #logic programming #source code
- Learning Logic Programs for Layout Analysis Correction (MB, MC, FE, DM), pp. 27–34.
- MLDM-2003-CeciAM
- Simplification Methods for Model Trees with Regression and Splitting Nodes (MC, AA, DM), pp. 20–34.