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Semantic Knowledge Engineering Approach

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Modeling with Rules Using Semantic Knowledge Engineering

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 130))

Abstract

In this chapter we introduce the Semantic Knowledge Engineering approach. It is a development approach for Knowledge-based Systems that uses rule-based knowledge representation. The core of the approach is the formalized rule representation method XTT. The motivation for the approach, along with its distinctive features are given. Then the SKE design process for rule-based systems is presented. SKE was developed to support a heterogeneous architecture of rule-based applications. The approach is well supported by a number of discussed software tools for knowledge base design, generation of the executable rule format, and execution of the rule-based system. Furthermore, tools for rule analysis are discussed.

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Notes

  1. 1.

    See http://hekate.ia.agh.edu.pl.

  2. 2.

    See http://geist.re/pub:projects:bimloq:start.

  3. 3.

    See http://geist.re/pub:projects:parnas:start.

  4. 4.

    Here by “quality” we mostly mean the correctness of the system, providing its safety, reliability, etc. From this perspective, quality is mostly assured by system verification.

  5. 5.

    In fact, one can imagine that a number of documents related to the system can be used in this phase. This include norms, standards, and written policies.

  6. 6.

    To simplify the transition from this stage to the next one, some basic natural language processing techniques might be considered. In fact, in [1] we explored a simple semi-formalization in Structured English, which is the part of the SBVR standard [2].

  7. 7.

    Considering the whole life cycle of a system more phases of the process could be identified, e.g. refinement, tuning, maintenance, etc. However, these are not directly addressed here, because the focus is on building the system.

  8. 8.

    It is worth emphasizing that the principal idea is not to model the whole application in the rule-based manner. Instead, it is asserted that a clear separation of the declarative rule-based logic is possible. Interfaces are identified and possibly designed in another, more common way e.g. using object-oriented frameworks.

  9. 9.

    See http://ai.ia.agh.edu.pl/wiki/hekate:cases:start.

  10. 10.

    See http://ai.ia.agh.edu.pl/wiki/hekate:cases:hekate_case_cashpoint.

  11. 11.

    See http://www.trolltech.com.

  12. 12.

    See http://www.swi-prolog.org/packages/jpl.

  13. 13.

    See http://www.swi-prolog.org/packages/xpce.

  14. 14.

    In fact the original case study does not have this deficiency. To show the discovery of uncovered states, the model domain has been changed and the number of failed attempts have been increased to 5.

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Authors and Affiliations

  1. AGH University of Science and Technology, Kraków, Poland

    Grzegorz J. Nalepa

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Nalepa, G.J. (2018). Semantic Knowledge Engineering Approach. In: Modeling with Rules Using Semantic Knowledge Engineering. Intelligent Systems Reference Library, vol 130. Springer, Cham. https://doi.org/10.1007/978-3-319-66655-6_9

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  • DOI: https://doi.org/10.1007/978-3-319-66655-6_9

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