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Guidelines for creating a rule-based knowledge learning system and their application to a Chinese business card layout analysis

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Abstract

Rule selection has long been a problem of great challenge that has to be solved when developing a rule-based knowledge learning system. Many methods have been proposed to evaluate the eligibility of a single rule based on some criteria. However, in a knowledge learning system there is usually a set of rules. These rules are not independent, but interactive. They tend to affect each other and form a rule-system. In such case, it is no longer reasonable to isolate each rule from others for evaluation. A best rule according to certain criterion is not always the best one for the whole system. Furthermore, the data in the real world from which people want to create their learning system are often ill-defined and inconsistent. In this case, the completeness and consistency criteria for rule selection are no longer essential. In this paper, some ideas about how to solve the rule-selection problem in a systematic way are proposed. These ideas have been applied in the design of a Chinese business card layout analysis system and gained a good result on the training data set of 425 images. The implementation of the system and the result are presented in this paper.

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Authors and Affiliations

  1. Institute of Machine Intelligence, Nankai University, 300071, Tianjin, P.R. China

    Pan Wumo & Wang Qingren

Authors
  1. Pan Wumo
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  2. Wang Qingren
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Correspondence to Pan Wumo.

Additional information

PAN Wumo received his B.S. degree in computational mathematics in 1995, and his M.S. degree in pattern recognition and intelligent control in 1998, both from Nankai University. He is currently a Ph.D. candidate in the Institute of Machine Intelligence at Nankai, University. Since 1997, he has been working on a document processing system—RTK, focusing on document layout analysis. His current research interests lie in the area of document image understanding, machine learning systems, intelligence control, and artificial intelligence. He is now a student member of the IEEE Systems, Man, and Cybernetics Society.

WANG Qingren, holding his Ph.D. degree in computer science and M.S. degree, in information theory, joined the faculty of computer science of Nankai University in 1984. He was a professor, Director of the Robotics Lab, and Vice Chairman in that, department before 1989. In 1990, he founded the Institute of Machine Intelligence, and became the Director. He became a senior member of IEEE in 1986. While maintaining his academic positions with Nankai University, he is currently the CEO and President of Exper Vision Inc., a high-tech company in the Silicon Valley, USA. Professor Wang’s research interests include OCR and documentation, robotics, computer game playing, and application of software technologies.

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Pan, W., Wang, Q. Guidelines for creating a rule-based knowledge learning system and their application to a Chinese business card layout analysis. J. Comput. Sci. & Technol. 16, 47–56 (2001). https://doi.org/10.1007/BF02948852

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  • DOI: https://doi.org/10.1007/BF02948852

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