Travelled to:1 × Egypt
1 × France
1 × Germany
1 × India
1 × Italy
1 × USA
1 × United Kingdom
Collaborated with:M.Maggini F.Cesarini G.Soda S.Marinai E.Francesconi ∅ M.Diligenti C.L.Giles A.Freno E.Trentin L.Sarti C.d.Mauro J.Sheng F.Scarselli F.Coetzee S.Lawrence I.G.Councill E.D.Iorio A.Pucci
Talks about:document (3) system (3) architectur (2) understand (2) random (2) graph (2) class (2) tree (2) use (2) likelihood (1)
Person: Marco Gori
DBLP: Gori:Marco
Contributed to:
2009
2007
2006
2004
2001
2000199919971995Wrote 12 papers:
- KDD-2009-FrenoTG #estimation #hybrid #pseudo #random #scalability
- Scalable pseudo-likelihood estimation in hybrid random fields (AF, ET, MG), pp. 319–328.
- ECIR-2007-Gori #learning
- Learning in Hyperlinked Environments (MG), p. 3.
- ECDL-2006-CouncillGIGMP #architecture #deployment #flexibility #generative #library #towards
- Towards Next Generation CiteSeer: A Flexible Architecture for Digital Library Deployment (IGC, CLG, EDI, MG, MM, AP), pp. 111–122.
- ICPR-v3-2004-GoriMS #graph #random #using
- Graph matching using Random Walks (MG, MM, LS), pp. 394–397.
- ICDAR-2001-DiligentiGMS #classification #documentation #html #modelling
- Classification of HTML Documents by Hidden Tree-Markov Models (MD, MG, MM, FS), pp. 849–853.
- ICDAR-2001-MauroGM #adaptation #information retrieval #visual notation
- APEX An Adaptive Visual Information Retrieval System (CdM, MG, MM), pp. 898–902.
- VLDB-2000-DiligentiCLGG #crawling #graph #using
- Focused Crawling Using Context Graphs (MD, FC, SL, CLG, MG), pp. 527–534.
- ICDAR-1999-CesariniFGS #approach #comprehension #documentation #multi
- A Two Level Knowledge Approach for Understanding Documents of a Multi-Class Domain (FC, EF, MG, GS), pp. 135–138.
- ICDAR-1999-CesariniGMS #documentation #representation #segmentation
- Structured Document Segmentation and Representation by the Modified X-Y tree (FC, MG, SM, GS), pp. 563–566.
- ICDAR-1997-CesariniFGMSS #architecture #recognition
- A Neural-Based Architecture for Spot-Noisy Logo Recognition (FC, EF, MG, SM, JS, GS), pp. 175–179.
- ICDAR-1997-CesariniFGMSS97a #comprehension
- Rectangle Labelling for an Invoice Understanding System (FC, EF, MG, SM, JS, GS), pp. 324–330.
- ICDAR-v2-1995-CesariniGMS
- A system for data extraction from forms of known class (FC, MG, SM, GS), pp. 1136–1140.