ADVANCES IN DOCUMENT CLASSIFICATION BY VOTING OF COMPETITIVE APPROACHES
Chantal-Kristin Wenzel, S. Baumann, T. Jager · Series in machine perception and artificial intelligence · 1998
This paper presents a complex approach for the content-based text categorization of printed German business letters into pre-defined message types such as order, invoice, offer, etc. The categorization results of two competing classifiers are combined by means of a voting component embodying knowledge about the strengths and weaknesses of the classifiers. The individual classifiers differ strongly in their basic assumptions: While the first one considers layout and typographic information with respect to certain keywords the second one is a more conventional text categorization approach which merely incorporates textual features. Since this whole categorization tool is embedded into a document analysis system, a highly precise classification is essential for a subsequent goal-directed extraction of structured information aimed at the integration of the document into the current business workflow of a company