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Travelled to:
1 × Belgium
1 × Brazil
1 × Canada
1 × India
1 × Japan
1 × Korea
1 × Switzerland
1 × The Netherlands
1 × United Kingdom
3 × Italy
3 × USA
7 × Germany
Collaborated with:
F.Esposito M.Ceci G.Semeraro A.Appice M.Berardi O.Altamura C.Loglisci F.A.Lisi N.Fanizzi S.Ferilli F.Fumarola L.Macchia T.Weninger J.Han G.Porcelli N.Barile A.Lanza P.Guccione A.Ciampi A.Muolo C.D.Antifora G.d.Gennaro C.Brunk M.J.Pazzani H.L.Viktor E.Paquet H.Guo C.Caruso C.Valente
Talks about:
learn (10) document (7) approach (5) relat (5) logic (5) mine (5) data (5) techniqu (4) analysi (4) machin (4)

Person: Donato Malerba

DBLP DBLP: Malerba:Donato

Contributed to:

MLDM 20122012
SAC 20122012
CIKM 20102010
SAC 20102010
MLDM 20092009
ICDAR 20072007
MLDM 20072007
ICDAR 20052005
ECIR 20032003
ICDAR 20032003
ICML 20032003
MLDM 20032003
ICDAR 20012001
MLDM 20012001
ICDAR 19991999
MLDM 19991999
ECDL 19971997
ICDAR 19971997
LOPSTR 19971997
ICDAR v1 19951995
LOPSTR 19951995
LOPSTR/META 19941994
ICDAR 19931993
SEKE 19931993

Wrote 28 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-2012-GuccioneCAMM #clustering #network
Trend cluster based interpolation everywhere in a sensor network (PG, AC, AA, DM, AM), pp. 827–828.
CIKM-2010-WeningerFHM #database #web
Mapping web pages to database records via link paths (TW, FF, JH, DM), pp. 1637–1640.
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.
MLDM-2009-LoglisciM #mining #multi
Mining Multiple Level Non-redundant Association Rules through Two-Fold Pruning of Redundancies (CL, DM), pp. 251–265.
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.
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.
ICDAR-2001-MalerbaELA #automation #component #comprehension #dependence #documentation #image #logic
Automated Discovery of Dependencies Between Logical Components in Document Image Understanding (DM, FE, FAL, OA), pp. 174–178.
MLDM-2001-MalerbaELL #first-order #induction #recognition
First-Order Rule Induction for the Recognition of Morphological Patterns in Topographic Maps (DM, FE, AL, FAL), pp. 88–101.
ICDAR-1999-AltamuraEM #adaptation #analysis #documentation #interactive
WISDOM++: An Interactive and Adaptive Document Analysis System (OA, FE, DM), pp. 366–369.
MLDM-1999-AltamuraELM #documentation #learning
Symbolic Learning Techniques in Paper Document Processing (OA, FE, FAL, DM), pp. 159–173.
ECDL-1997-SemeraroEMFF #library #machine learning #online
Machine Learning + On-line Libraries = IDL (GS, FE, DM, NF, SF), pp. 195–214.
ICDAR-1997-EspositoMSAG #library #machine learning #semantics
Information Capture and Semantic Indexing of Digital Libraries through Machine Learning Techniques (FE, DM, GS, CDA, GdG), pp. 722–727.
LOPSTR-1997-SemeraroEMFF #datalog #framework #incremental #induction #logic #synthesis
A Logic Framework for the Incremental Inductive Synthesis of Datalog Theories (GS, FE, DM, NF, SF), pp. 300–321.
ICDAR-v1-1995-EspositoMS #analysis #approach #knowledge-based #layout
A knowledge-based approach to the layout analysis (FE, DM, GS), pp. 466–471.
LOPSTR-1995-SemeraroEM #datalog #refinement #source code
Ideal Refinement of Datalog Programs (GS, FE, DM), pp. 120–136.
LOPSTR-1994-SemeraroEMBP #case study #learning #logic #source code
Avoiding Non-Termination when Learning Logical Programs: A Case Study with FOIL and FOCL (GS, FE, DM, CB, MJP), pp. 183–198.
ICDAR-1993-EspositoMS #automation #comprehension #documentation
Automated acquisition of rules for document understanding (FE, DM, GS), pp. 650–654.
SEKE-1993-EspositoMS #information management #machine learning #refinement
Machine Learning Techniques for Knowledge Acquisition and Refinement (FE, DM, GS), pp. 319–323.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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