caa a22 4500 475799305 CHVBK 20180406123733.0 cr unu---uuuuu 170329e20000301xx s 000 0 eng 10.1023/A:1008735902918 doi (NATIONALLICENCE)springer-10.1023/A:1008735902918 Machine Learning for Intelligent Processing of Printed Documents [Elektronische Daten] [Floriana Esposito, Donato Malerba, Francesca Lisi] A paper document processing system is an information system component which transforms information on printed or handwritten documents into a computer-revisable form. In intelligent systems for paper document processing this information capture process is based on knowledge of the specific layout and logical structures of the documents. This article proposes the application of machine learning techniques to acquire the specific knowledge required by an intelligent document processing system, named WISDOM++, that manages printed documents, such as letters and journals. Knowledge is represented by means of decision trees and first-order rules automatically generated from a set of training documents. In particular, an incremental decision tree learning system is applied for the acquisition of decision trees used for the classification of segmented blocks, while a first-order learning system is applied for the induction of rules used for the layout-based classification and understanding of documents. Issues concerning the incremental induction of decision trees and the handling of both numeric and symbolic data in first-order rule learning are discussed, and the validity of the proposed solutions is empirically evaluated by processing a set of real printed documents. Kluwer Academic Publishers, 2000 learning and knowledge discovery nationallicence intelligent information systems nationallicence intelligent document processing nationallicence decision-tree learning nationallicence first-order rule induction nationallicence Esposito Floriana Dipartimento di Informatica, Università degli Studi di Bari, via Orabona 4, 70125, Bari, Italy aut Malerba Donato Dipartimento di Informatica, Università degli Studi di Bari, via Orabona 4, 70125, Bari, Italy aut Lisi Francesca Dipartimento di Informatica, Università degli Studi di Bari, via Orabona 4, 70125, Bari, Italy aut Journal of Intelligent Information Systems Kluwer Academic Publishers 14/2-3(2000-03-01), 175-198 0925-9902 14:2-3<175 2000 14 10844 https://doi.org/10.1023/A:1008735902918 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1008735902918 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Esposito Floriana Dipartimento di Informatica, Università degli Studi di Bari, via Orabona 4, 70125, Bari, Italy aut NATIONALLICENCE 700 1- Malerba Donato Dipartimento di Informatica, Università degli Studi di Bari, via Orabona 4, 70125, Bari, Italy aut NATIONALLICENCE 700 1- Lisi Francesca Dipartimento di Informatica, Università degli Studi di Bari, via Orabona 4, 70125, Bari, Italy aut NATIONALLICENCE 773 0- Journal of Intelligent Information Systems Kluwer Academic Publishers 14/2-3(2000-03-01), 175-198 0925-9902 14:2-3<175 2000 14 10844 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer