Advertisement

Exploring RDF for Expertise Matching within an Organizational Memory

  • Ping Liu
  • Jayne Curson
  • Peter Dew
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2348)

Abstract

Organizations have realized that effective development and management of their organizational knowledge base is very important for their survival in todays competitive business environment. People, as a special knowledge asset, also attract the interest of many researchers because, only through people communicating with one another, can they really share their tacit knowledge and skills that can be more valuable than explicit documentation. The need to be able to quickly locate experts among the heterogeneous data sources stored in the organizational memory has been recognized by many researchers. This paper examines the advantages of using RDF (Resource Description Framework) for Expertise Matching. The major challenge is to semantically integrate heterogeneous data sources stored in the organizational memory and facilitate users to locate the right people. We present a practical application of this using a case study where PhD applicants can locate potential supervisors before they formally apply to a university.

Keywords

Tacit Knowledge Resource Description Framework Organizational Memory Resource Description Framework Data Heterogeneous Data Source 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Abecker, A. and Decker, S. Organizational Memory: Knowledge Acquisition, Integration, and Retrieval Issues in Knowledge-Based Systems, Lecture Notes in Artificial Intelligence, Vol. 1570, Springer-Verlag, Verlin, Heidelberg, pages 113–124,(1999)Google Scholar
  2. 2.
    Ackerman, M. S. and Halverson, C, Considering an Organization’s Memory, in Conference on CSCW’98 pages 39–48, ACM Press, Seattle, WA, (1998)Google Scholar
  3. 3.
    Baeze-Yates, R. and Ribeiro-Neto, B., Modern information retrieval Imprint Addison-Wesley Longman (1999)Google Scholar
  4. 4.
    Bannon, L. and Kuuti, K. Shifting Perspective on Organizational Memory From Storage to Active Remembering in Proceeding of the HICSS’96, IEEE Computer Press, (1996), 156–167Google Scholar
  5. 5.
    Bedard, J. Expertise and its Relation to Audit Decision Quality, Contemporary Accounting Research, Fall, pp. 198–222 (1991)Google Scholar
  6. 6.
    Bennis, W., Organizing genius: the secrets of creative collaboration Addison-Wesley: Reading, Mass. (1997)Google Scholar
  7. 7.
    Berners-Lee, T., Why RDF model is different form the XML model (1998) available online: http://www.w3.org/DesignIssues/RDF-XML.html
  8. 8.
    Bishr, Y., Kuhn, W. Ontology-Based Modelling of Geospatial Information 3rd AGILE Conference on Geographic Information Science, Finland, May 25th-2th, (2000)Google Scholar
  9. 9.
    Bishop, K., Heads or Tales: Can Tacit Knowledge Really be Managed Proceeding of ALIA (2000) Biennial Conference, 23–26 October, Canberra, available online at http://www.alia.org.au/conferences/alia2000/proceedings/karen.bishop.html
  10. 10.
    Bray, T., Paoli, J., Sperberg-McQueen, C, and Maler, E., Extensible Markup Language (XML) 1.0. W3C Recommendation, 6-October-2000. http://www.w3.org/TR/REC-xml
  11. 11.
    Brickley, D. and Guha, R.V., Resource Description Framework (RDF) Schema Specification 1.0, W3C Candidate Recommendation, World Wide Web Consortium, (2000), http://www.w3.org/TR/rdf-schema
  12. 12.
    Busse, S., Kutsche, R., Leser, U., and Weber, H. Federated Information Systems: Concepts, Terminology and Architectures Forschungsberichte des Fachbereichs Informatik 99-9, (1999) available online at http://citeseer.nj.nec.com/busse99federated.html
  13. 13.
    Clark, J. XSL Transformations (XSLT) Version 1.0 W3C Recommendation 16 November 1999, http://www.w3.org/TR/xslt.html
  14. 14.
    Clark, P., Thompson, J., Holmback, H., and Duncan, L. Exploiting a Thesaurus-Based Semantic Net for Knowledge-Based Search In Proceeding 12th Conference on Innovative Applications of AI (AAAI/IAAT’OO), (2000), 988–995Google Scholar
  15. 15.
    Cross, R. and Baird, L., Technology Is Not Enough: Improving Performance by Building Organizational Memory MIT Sloan Management Review Spring (2000) Vol. 41, No. 3 page 69–78Google Scholar
  16. 16.
    Cui, Z., Tamma, V., and Bellifemine, F. Ontology management in enterprises BT Technology Journal Vol. 17 No 4 October (1999)Google Scholar
  17. 17.
    Davenport, T. H. and Prusak, L. Working Knowledge: how organizations manage what they know Boston, Mass, Harvard Business School Press, (1998)Google Scholar
  18. 18.
    Davies, N. J., Stewart, S. and Weeks, R, Knowledge Sharing Agents over the World Wide Web, WebNet’ 98, Florida, USA, November (1998)Google Scholar
  19. 19.
    Decker, S., Mitra, P., and Melnik, S., Framework for the Semantic Web: an RDF tutorial. IEEE Internet Computing, 4(6), November/December, (2000), 68–73Google Scholar
  20. 20.
    Eppler, M.J. Making Knowledge Visible Through Intranet Knowledge Maps: Concepts, Elements, Cases System Sciences, Proceedings of the 34th Annual Hawaii International Conference, (2001), 1530–1539Google Scholar
  21. 21.
    Fensel, D., Angele, J., Decker, S., Erdmann, M., Schnurr, H. P., Staab, S., Studer, R., and Witt, A., On2broker: Semantic-based access to information sources at the WWW in World Conference on the WWW and Internet (WebNet99), Honolulu, Hawaii, (1999)Google Scholar
  22. 22.
    Frensch, P. A. and Sternberg, R. J. Expertise and Intelligent Thinking: When is it Worse to Know Better, Sternberg, R. (ed.), Advances in the Psychology of Human Intelligence, pp. 157–188 (1989)Google Scholar
  23. 23.
    Gaines, B. R. The Collective Stance in Modeling Expertise in Individuals and Organizations, available online at http://ksi.cpsc.ucalgary.ca/articles/Collective/Collective2.html
  24. 24.
    Garcia-Molina, H., Papakonstantinou, Y., Quass, D., Rajaraman, A., Sagiv, Y., Ullman, J., and Widom, J. The tsimmis approach to mediation: Data models and languages. In Next Generation Information Technologies and Systems (NGITS-95), Naharia, Israel, November 1995. Extended AbstractGoogle Scholar
  25. 25.
    Gibson, R. ed 1996 Rethinking the Future Nicholas Brealey Publishing: LondonGoogle Scholar
  26. 26.
    Heflin, J. and Hendler, J. Searching the Web with SHOE In Artificial Intelligence for Web Search. Papers from the AAAI Workshop. WS-00-01, pages 35–40. AAAI Press, (2000)Google Scholar
  27. 27.
    Horvath, J., Working with Tacit Knowledge available online at http://www-4.ibm.com/software/data/knowledge/media/tacit_knowledge.pdf
  28. 28.
    Hunter, J. and Lagoze, C, Combining RDF and XML Schemas to Enhance Interoperability Between Metadata Application Profiles Tenth International World Wide Web Conference, HongKong, May (2001)Google Scholar
  29. 29.
    Karvounarakis, G., Christophides, V., and Plexousakis, D., Querying Semi-structured (Meta)Data and Schemas on the Web: The case of RDF & RDFS Technical Report 269, ICS-FORTH, (2000). available at http://www.ics.forth.gr/ proj/isst/RDF/rdfquerying.pdf
  30. 30.
    Lassila, O. and Swick, R., Resource Description Framework (RDF) Model and Syntax Specification; World Wide Web Consortium Recommendation http://www.w3.org/TR/REC-rdf-syntax/
  31. 31.
    Liao, M., Hinkelmann, K., Abecker, A., and Sintek, M. A Competence Knowledge Base System as Part of the Organizational Memory In: Frank Puppe (ed.) XPS-99 / 5. Deutsche Tagung Wissensbasierte Systeme, Würzburg, Springer Verlag, LNAI1570, March (1999)Google Scholar
  32. 32.
    Marchant, G. Analogical Reasoning and Hypothesis Generation in Auditing, The Accounting Review 64, July, pp. 500–513, (1989)Google Scholar
  33. 33.
    Rabarijaona, A., Dieng, R., Corby, O., and Ouaddari, R. Building and Searching XML-based Corporate Memory IEEE Intelligent Systems and their Applications, Special Issue on Knowledge Management and the Internet, May/June (2000) 56–63Google Scholar
  34. 34.
    Seligman, L. and Rosenthal, A. The Impact of XML on Databases and Data Sharing, IEEE Computer (2001)Google Scholar
  35. 35.
    Sheth, A. Changing Focus on Interoperability in Information Systems: from System, Syntax, Structure to Semantics, in Interoperating Geographic Information Systems, M. F. Goodchild, M. J. Egenhofer, R. Fegeas, and C. A. Kottman (eds.), Kluwer, (1998)Google Scholar
  36. 36.
    Stewart, T. In interview Tom Stewart on Intellectual Capital Knowledge Inc., May (1997) available online at: http://webcom/quantera/llstewart.html
  37. 37.
    Stuckenschmidt, H., Using OIL for Intelligent Information Integration In Proceedings of the Workshop on Applications of Ontologies and Problem-Solving Methods at ECAI (2000)Google Scholar
  38. 38.
    Vdovjak, R., and Houben, G. RDF Based Architecture for Semantic Integration of Heterogeneous Information Sources Workshop on Information Integration on the Web (2001) 51–57Google Scholar
  39. 39.
    Wellins, R. S., Byham, W. C., and Wilson, J. M. Empowered Teams: creating self-directed work groups that improve quality, productivity, and participation Jossey-Bass: San Francisco (1993)Google Scholar
  40. 40.
    Yimam, D. Expert Finding Systems for Organizations: Domain Analysis and the DEMOIR approach ECSCW 99 Beyond Knowledge Management: Management Expertise Workshop, (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Ping Liu
    • 1
  • Jayne Curson
    • 1
  • Peter Dew
    • 1
  1. 1.Informatics Research Institute, School of ComputingUniversity of LeedsLeedsUK

Personalised recommendations