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» A Grammar Combining Phrase Structure and Field Structure
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ACL
2006
14 years 11 months ago
Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling
We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
ECIR
2007
Springer
14 years 11 months ago
Multinomial Randomness Models for Retrieval with Document Fields
Document fields, such as the title or the headings of a document, offer a way to consider the structure of documents for retrieval. Most of the proposed approaches in the literatu...
Vassilis Plachouras, Iadh Ounis
ICDAR
2003
IEEE
15 years 3 months ago
Numerical Sequence Extraction in Handwritten Incoming Mail Documents
In this communication, we propose a method for the automatic extraction of numerical fields in handwritten documents. The approach exploits the known syntactic structure of the nu...
Guillaume Koch, Laurent Heutte, Thierry Paquet
LREC
2008
110views Education» more  LREC 2008»
14 years 11 months ago
Unsupervised and Domain Independent Ontology Learning: Combining Heterogeneous Sources of Evidence
Acquiring knowledge from the Web to build domain ontologies has become a common practice in the Ontological Engineering field. The vast amount of freely available information allo...
David Manzano-Macho, Asunción Gómez-...
ICPR
2002
IEEE
15 years 10 months ago
Multicue MRF Image Segmentation: Combining Texture and Color Features
Herein, we propose a new Markov random field (MRF) image segmentation model which aims at combining color and texture features. The model has a multi-layer structure: Each feature...
Zoltan Kato, Ting-Chuen Pong, Song Guo Qiang