An experimental page layout recognition system for office document automatic classification: an integrated approach for inductive generalization

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Abstract
A novel approach to automatic classification of digitized office documents based on the inductive generalization of their layout style, is presented. It is supported by the observation that for a number of printed documents it is possible to find a set of relevant and invariant layout features. These are geometrical characteristics automatically detected through a segmentation and layout analysis process. The learning step, in which significant examples of document classes are used to train the classification system, involves the novel idea of integrating parametric (numerical) and conceptual (symbolic) learning methods.<>

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