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Semantic Annotations for Mediation of Complex Rule Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

Abstract

Design of Business Intelligence systems capable of effectively handling a domain knowledge is a well known, but currently not solved challenge for both Software and Knowledge Engineers. There exist several approaches to extract and model the Business Knowledge, most notably Business Processes and Business Rules. However, each of them has its own weaknesses and therefore it is often desirable to build hybrid models composed of several knowledge representations. In this paper we describe an extension to Business Rules in order to facilitate creation of such heterogeneous systems. This is achieved by introducing semantic annotations to existing rule modeling languages. We also present how the additional semantic information is leveraged in the Prosecco project.

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Notes

  1. 1.

    See http://prosecco.agh.edu.pl for the project website.

  2. 2.

    For more information, please see: https://www.w3.org/TR/owl-semantics/.

  3. 3.

    HMR stands for HeKaTe Meta Representation, a human readable format to represent XTT2 models. For a detailed specification of the language see: http://glados.kis.agh.edu.pl/doku.php?id=pub:software:heartdroid:documentation:hmr.

  4. 4.

    For more details on the annotation system in Java see: http://docs.oracle.com/javase/specs/jls/se8/html/jls-9.html#jls-9.7.

  5. 5.

    For a full listing of Jena’s capabilities see: https://jena.apache.org/.

  6. 6.

    For a complete specification, see: https://www.w3.org/TR/sparql11-query/.

  7. 7.

    Protege is an ontology editor. For details see http://protege.stanford.edu/.

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Correspondence to Krzysztof Kutt .

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Ślażyński, M., Nalepa, G.J., Bobek, S., Kutt, K. (2017). Semantic Annotations for Mediation of Complex Rule Systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_56

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  • DOI: https://doi.org/10.1007/978-3-319-59060-8_56

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