Abstract
WISDOM is a intelligent document processing system that transforms printed information into a symbolic representation. Its distinguishing feature is the use of a rule base which is automatically built from a set of training documents using two inductive learning techniques: Decision tree learning for the blocks classification, and first-order rule induction for the document classification and understanding. In the paper, advances made with respect to previous studies on this application domain are illustrated and a complete set of experimental results is reported.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Ciardiello, G., Scafuro, G., Degrandi, M.T., Spada, M.R., Roccotelli, M.P.: An Experimental System for Office Document Handling and Text Recognition. Proc. of the 9th Int. Conf. on Pattern Recognition, IEEE Computer Society Press, Los Alamitos (1988) 739–743.
De Raedt, L.: Inductive Theory Revision, Academic Press, London (1992).
Esposito, F., Malerba, D., Semeraro, G., Annese, E., Scafuro, G.: Empirical Learning Methods for Digitized Document Recognition: An Integrated Approach to Inductive Generalization. Proc. of the 6th IEEE Conf. on Artificial Intelligence Applications, IEEE Computer Society Press, Los Alamitos (1990) 37–45.
Esposito, F., Malerba, D., Semeraro, G.: Multistrategy Learning for Document Recognition. Applied Artificial Intelligence, 8(1) (1994) 33–84.
Esposito, F., Malerba, D., Semeraro, G.: A Comparative Analysis of Methods for Pruning Decision Trees. IEEE Trans. on Pattern Analysis and Machine Intelligence, TPAMI-19(5) (1997) 476–491.
Fayyad, U.M., Irani, K.B.: On the Handling of Continuous-Valued Attributes in Decision Tree Generation. Machine Learning, 8 (1992) 87–102.
Fisher, J.L., Hinds, S.C., D’Amato, D.P.: A Rule-Based System for Document Image Segmentation. Proc. of the 10th Int. Conf. on Pattern Recognition, IEEE Computer Society, Los Alamitos (1990) 567–572.
Helft, N.: Inductive Generalization: A Logical Framework. In: Bratko, I., Lavrac, N. (eds.): Progress in Machine Learning—Proc. of the EWSL87, Sigma Press, London (1987) 149–157.
Malerba, D., Semeraro, G., Bellisari, E.: LEX: A Knowledge-Based System for the Layout Analysis. Proc. of the 3rd Int. Conf. on the Practical Application of Prolog (1995) 429–443.
Malerba, D., Semeraro, G., Esposito, F.: A Multistrategy Approach to Learning Multiple Dependent Concepts. In: Taylor, C., Nakhaeizadeh, R. (eds.): Machine Learning and Statistics: The Interface, Wiley, London (1997) 87–106.
Malerba, D., Esposito, F., Semeraro, G., Caggese, S.: Handling Continuous Data in Top-Down Induction of First-Order Rules. In: Lenzerini, M. (ed.): AI * IA 97: Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence, Vol. 1321, Springer-Verlag, Berlin Heidelberg New York (1997) 24–35.
Malerba, D., Esposito, F., Semeraro, G., De Filippis, L.: Processing Paper Documents in WISDOM. In: Lenzerini, M. (ed.): AI * IA 97: Advances in Artificial Intelligence, Lecture Notes in Artificial Intelligence, Vol. 1321, Springer-Verlag, Berlin Heidelberg New York (1997) 439–442.
Nagy, G., Seth, S.C., Stoddard, S.D.: A Prototype Document Image Analysis System for Technical Journals. IEEE Computer, 25(7) (1992) 10–22.
Orkin, M., Drogin, R.: Vital Statistics, McGraw Hill, New York (1990).
Quinlan, J.R.: C4.5: Programs for Machine Learning, Morgan Kaufmann, San Mateo (1993).
Quinlan, J.R., Cameron-Jones, R.M.: FOIL: A Midterm Report. In: Brazdil, P.B. (ed.): Machine Learning: ECML-93, Lecture Notes in Artificial Intelligence, Vol. 667, Berlin: Springer-Verlag, Berlin Heidelberg New York (1993) 3–20.
Srihari, S.N., Lam, S.W., Hull, J.J., Srihari, R.K., Govindaraju, V.: Intelligent Data Retrieval from Raster Images of Documents. In: Fox, E.A. (ed.): Source Book on Digital Libraries, ftp://fox.cs.vt.edu/pub/DigitalLibrary (1993).
Tang, Y.Y., Yan, C.D., Suen, C.Y.: Document Processing for Automatic Knowledge Acquisition, IEEE Trans. on Knowledge and Data Engineering, 6(1) (1994) 3–21.
Utgoff, P.E.: An Improved Algorithm for Incremental Induction of Decision Trees. Proc. of the 11th Int. Conf. on Machine Learning, Morgan Kaufmann, San Francisco (1994) 318–325.
Wang, D., Srihari, R.N.: Classification of Newspaper Image Blocks Using Texture Analysis. Computer Vision, Graphics, and Image Processing, 47 (1989) 327–352.
Wong, K.Y., Casey, R.G., Wahl, F.M.: Document Analysis System, IBM J. of Research Development, 26(6) (1982) 647–656.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Esposito, F., Malerba, D., Lisi, F.A. (1999). Machine learning for intelligent document processing: The WISDOM system. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1999. Lecture Notes in Computer Science, vol 1609. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095095
Download citation
DOI: https://doi.org/10.1007/BFb0095095
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65965-5
Online ISBN: 978-3-540-48828-6
eBook Packages: Springer Book Archive