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This paper proposes an entity recognition system in image documents recognized by OCR. The system is based on a graph matching technique and is guided by a database describing the entities in its records. The input of the system is a document which is labeled by the entity attributes. A first grouping of those labels based on a function score leads to a selected set of candidate entities. The entity...
This paper describes a method for extracting relevant tokens of entity from semi-structured administrative documents. This method is used for mislabeling correction by employing the entity tokens physically close in a document. Firstly, the entities are labeled. Secondly, each entity is modeled by a tokens structure graph in which the nodes represent the tokens and the arcs represent the distances...
This paper proposes an entity local structure comparison approach based on inexact subgraph matching. The comparison results are used for mislabeling correction in the local structure. The latter represents a set of entity attribute labels which are physically close in a document image. It is modeled by an attributed graph describing the content and presentation features of the labels by the nodes...
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