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Ontology and Rule Based Inferring on Project Teams

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7547))

Abstract

A task of automatic identification of potential project team members based on project requirements and personal competence profiles is a complex one. It requires a good knowledge base together with an adequate knowledge processing engine, capable of inferring on the knowledge available. In this paper, we study and present an approach to implement a knowledge management system with the use of semantic web technologies in combination with a declarative production rule-based system. We used ontologies to represent the needed knowledge and rule-based expert system to infer on the knowledge and to provide the requested results. In this manner we developed a prototype system that should assist in project team building activities.

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References

  1. Passin, T.B.: Explorers guide to Semantic Web. Manning, Greenwich (2004)

    Google Scholar 

  2. Berners-Lee, T.: Business Model for the Semantic Web (2001), http://www.w3.org/DesignIssues/Business

  3. Manola, F., Miller, E. (eds.): RDF Primer. W3C Consortium recommendation (2004)

    Google Scholar 

  4. Lassila, O., Swick, R.R.: Resource Description Framework (RDF) Model and Syntax Specification. W3C Consortium (1999)

    Google Scholar 

  5. McGuiness, D.L., Harmelen, F. (eds.): OWL Web Ontology Language Overview. W3C Consortium recommendation (2004)

    Google Scholar 

  6. Bechhofer, S., Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D.L., Patel-Schneider, P.F., Stein, L.A.: OWL Web Ontology Language Reference. W3C Consortium (2004)

    Google Scholar 

  7. Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M.: SWRL: A Semantic Web Rule Language Combining OWL and RuleML. W3C Consortium (2004), http://www.w3.org/Submission/SWRL/

  8. Gruber, T.R.: Towards Principles for the Design of Ontologies used for Knowledge Sharing. In: Guarino, N., Poli, R. (eds.) Proc. International Workshop on Formal Ontology, Padova, Italy (1993)

    Google Scholar 

  9. Francis, D., Young, D.: Improving Work Groups: A Practical Manual for Team Building. University Associates, San Diego (1979)

    Google Scholar 

  10. Lau, T., Sure, Y.: Introducing Ontology-based Skills Management at a large Insurance Company. In: Modellierung 2002: Modellierung in der Praxis – Modellierung für die Praxis, pp. 123–134 (2002)

    Google Scholar 

  11. Biesalski, E., Abecker, A.: Integrated Processes and Tools for Personnel Development. In: 11th International Conference on Concurrent Enterprising, University BW Munich (2005)

    Google Scholar 

  12. Stader, J., Macintosh, A.: Capability Modelling and Knowledge Management. In: Applications and Innovations in Expert Systems VII, ES1999 – 19th Int. Conf. of the BCS Specialist Group on Knowledge-Based Systems and Applied Artificial Intelligence, pp. 33–50. Springer, Berlin (1999)

    Google Scholar 

  13. Jarvis, P., Stader, J., Macintosh, A., Moore, J., Chung, P.: What Right Do You Have to Do That? In: Proceedings of the 1st International Conference on Enterprise Information Systems, ICEIS, Portugal (1999)

    Google Scholar 

  14. Liao, M., Hinkelmann, K., Abecker, A., Sintek, M.: A Competence Knowledge Base System as Part of the Organizational Memory. In: Puppe, F. (ed.) XPS 1999. LNCS (LNAI), vol. 1570, pp. 125–137. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  15. Sure, Y., Maedche, A., Staab, S.: Leveraging Corporate Skill Knowledge - From ProPer to OntoProPer. In: Mahling, D., Reimer, U. (eds.) Proceedings of the 3rd International Conference on Practical Aspects of Knowledge Management (2000)

    Google Scholar 

  16. Colucci, S., Di Noia, T., Di Sciascio, E., Donini, F.M., Mongiello, M., Mottola, M.: A Formal Approach to Ontology-Based Semantic Match of Skills Descriptions. Journal of Universal Computer Science 9(12), 1437–1454 (2003)

    Google Scholar 

  17. Jena – A Semantic Web Framework for Java, http://jena.sourceforge.net/

  18. CLIPS – A Tool for Building Expert Systems, http://www.ghg.net/clips/CLIPS.html

  19. JClips — CLIPS for Java, http://www.cs.vu.nl/~mrmenken/jclips/

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Podgorelec, V. (2012). Ontology and Rule Based Inferring on Project Teams. In: Cipolla-Ficarra, F., Veltman, K., Verber, D., Cipolla-Ficarra, M., Kammüller, F. (eds) Advances in New Technologies, Interactive Interfaces and Communicability. ADNTIIC 2011. Lecture Notes in Computer Science, vol 7547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34010-9_5

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  • DOI: https://doi.org/10.1007/978-3-642-34010-9_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34009-3

  • Online ISBN: 978-3-642-34010-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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