World Wide Web

, Volume 13, Issue 1–2, pp 75–103 | Cite as

A Human-Centered Semantic Service Platform for the Digital Ecosystems Environment

  • Hai Dong
  • Farookh Khadeer Hussain
  • Elizabeth Chang
Article

Abstract

Digital Ecosystems (DEST) have emerged with the purpose of enhancing communications among small and medium enterprises (SMEs) within the worldwide Business Ecosystem. However, because of the diversity and heterogeneity of the services in the DEST environment, existing commercial products or research outputs cannot be directly applied to this field so as to fulfill the requirements of SMEs. Human-centered computing has been applied to many areas, such as social classification, community-based ontology evolution, and more importantly, human-centered systems. In this paper, we propose a framework for a human-centered semantic service platform, in order to address the issue in the DEST environment. This framework incorporates the features of human-centered metadata publishing, maintenance and clustering, community-based ontology revolution and human-centered service retrieval, evaluation and ranking. To thoroughly validate the framework, we implement a prototype in the transport service domain, and conduct a series of evaluation experiments on the basis of this prototype.

Keywords

digital ecosystems (abbreviated as DEST) human-centered computing human-centered systems ontology revolution QoS evaluation service platform 

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References

  1. 1.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley, New York (1999)Google Scholar
  2. 2.
    Barrett, R., Maglio, P.P.: Intermediaries: new places for producing and manipulating web content. Comput. Netw. ISDN Syst. 30, 509–518 (1998)CrossRefGoogle Scholar
  3. 3.
    Barrett, R., Maglio, P.P.: Intermediaries: an approach to manipulating information streams. IBM Syst. J. 38, 629–641 (1999)CrossRefGoogle Scholar
  4. 4.
    Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scientific American Magazine. Scientific American, Inc., New York (2001)Google Scholar
  5. 5.
    Bianchini, D., Antonellis, V.D., Melchiori, M.: Flexible semantic-based service matchmaking and discovery. World Wide Web 11, 227–251 (2008)CrossRefGoogle Scholar
  6. 6.
    Bogers, T., Thoonen, W., Bosch, A.v.d.: Expertise classification: Collaborative classification vs. automatic extraction. In: Furner, J., Tennis, J.T. (eds.): the 17th ASIS&T SIG/CR Classification Research Workshop, Vol. 17, Austin (2006)Google Scholar
  7. 7.
    Chang, E., West, M.: Digital Ecosystem—A next generation of the collaborative environment. iiWAS2006, Yogyakarta (2006)Google Scholar
  8. 8.
    Chang, E., Dillon, T.S., Hussain, F.: Trust and Reputation for Service Oriented Environments-Technologies for Building Business Intelligence and Consumer Confidence. Wiley, West Sussex, UK (2005)Google Scholar
  9. 9.
    Chang, E., Hussain, F.K., Dillon, T.S.: CCCI Metrics for the measurement of quality of e-service. The 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’05). IEEE CS, France (2005)Google Scholar
  10. 10.
    Chang, E., Quaddus, M., Ramaseshan, R.: The vision of DEBI Institute: digital ecosystems and business intelligence: Digital Ecosystem and Business Intelligence Institute. DEBII, Perth (2006)Google Scholar
  11. 11.
    Chen, Y.-F., Huang, H., Jana, R., Jim, T., Hiltunen, M., John, S., Jora, S., Muthumanickam, R., Wei, B.: iMobile EE: an enterprise mobile service platform. Wirel. Netw. 9, 283–297 (2003)CrossRefGoogle Scholar
  12. 12.
    Cibrán, M.A., Verheecke, B., Vanderperren, W., Suvée, D., Jonckers, V.: Aspect-oriented programming for dynamic web service selection, integration and management. World Wide Web 10, 211–242 (2007)CrossRefGoogle Scholar
  13. 13.
    Conradi, R., Fernström, C., Fuggetta, A.: Concepts for evolving software processes. In: Finkelstein, A., Kramer, J., Nuseibeh, B.A. (eds.) Software Process Modeling and Technology. Research Studies, Chichester (1994)Google Scholar
  14. 14.
    Cugola, G., Nitto, E.D., Fuggetta, A., Ghezzi, C.: A framework for formalizing inconsistencies and deviations in human-centered systems. ACM Trans. Softw. Eng. Methodol. 5, 191–230 (1996)CrossRefGoogle Scholar
  15. 15.
    Dong, H., Hussain, F.K., Chang, E.: A semantic crawler based on an extended CBR algorithm. In: Meersman, R., Tari, Z., Herrero, P. (eds.) Lecture Notes in Computer Science: OTM 2008 Workshops, vol. 5333, pp. 1084–1093. Springer-Verlag, Berlin (2008)Google Scholar
  16. 16.
    Dong, H., Hussain, F.K., Chang, E.: A Transport Service Ontology-Based Focused Crawler. SKG 2008, pp. 48–55. IEEE, Beijing (2008)Google Scholar
  17. 17.
    Dong, H., Hussain, F.K., Chang, E.: Quality of service (QoS) based service retrieval engine. In: Gabriele Kotsis, D.T., Eric, Pardede, Ismail, Khalil (eds.) The 6th International Conference on Advances in Mobile Computing and Multimedia (MoMM 2008), pp. 405–408. ACM, Linz (2008)CrossRefGoogle Scholar
  18. 18.
    Dong, H., Hussain, F.K., Chang, E.: Transport Service Ontology and its Application in the Field of Semantic search. 2008 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI 2008), pp. 820–824. IEEE, Beijing (2008)Google Scholar
  19. 19.
    Furnas, G.W., Deerwester, S., Dumais, S.T., Landauer, T.K., Harshman, R.A., Streeter, L.A., Lochbaum, K.E.: Information retrieval using a singular decomposition model of latent semantic structure. 11th ACM SIGIR Conference on Research and Development in Information Retrieval (1988) 465–480Google Scholar
  20. 20.
    IBM: WebSphere application server. http://www-01.ibm.com/software/webservers/appserv/was/
  21. 21.
    Gendarmi, D., Lanubile, F., et al.: Community-driven ontology evolution based on folksonomies. In: Meersman, R., Tari, Z., Herrero, P. (eds.) On the move to meaningful internet systems 2006: OTM 2006 Workshops, pp. 181–188. Springer-Verlag, Berlin (2006)CrossRefGoogle Scholar
  22. 22.
    Grieco, R., Malandrino, D., Scarano, V.: A scalable cluster-based infrastructure for edge-computing services. World Wide Web 9, 317–341 (2006)CrossRefGoogle Scholar
  23. 23.
    Hayes, P.: RDF semantics. http://www.w3.org/TR/rdf-mt/ (2004)
  24. 24.
    Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS Quarterly 28, 75–105 (2004)Google Scholar
  25. 25.
    Hoffman, R.: Human-centered computing principles for advanced decision architectures. Army Research Laboratory (2004)Google Scholar
  26. 26.
    Hussain, F.K., Chang, E., Dillon, T.S.: Trustworthiness and CCCI metrics in P2P communication. Int. J. Comput. Syst. Sci. Eng. 19, 173–190 (2004)Google Scholar
  27. 27.
    Jaimes, A., Sebe, N., Gatica-Perez, D.: Human-centered computing: A multimedia perspective. MM’06, Santa Barbara (2006)Google Scholar
  28. 28.
    Karp, A.H.: Lessons from E-speak. HP Laboratories, Palo Alto (2004)Google Scholar
  29. 29.
    Liu, D.R., Shen, M., Liao, C.T.: Designing a composite e-service platform with recommendation function. Comput. Stand. Interfaces 25, 103–117 (2003)CrossRefGoogle Scholar
  30. 30.
    Martin, D.L., Burstein, M.H., McDermott, D.V., McIlraith, S.A., Paolucci, M., Sycara, K.P., McGuinness, D.L., Sirin, E., Srinivasan, N.: Bringing semantics to web services with OWL-S. World Wide Web 10, 243–277 (2007)CrossRefGoogle Scholar
  31. 31.
    Mathes, A.: Folksonomies: Cooperative Classification and Communication Through Shared Metadata. University of Illinois Urbana-Champaign, Champaign (2004)Google Scholar
  32. 32.
    Moore, J.F.: Predators and prey: a new ecology of competition. Harvard Bus. Rev. 71, 75–86 (1993)Google Scholar
  33. 33.
    Mukherjee, S., Ramakrishnan, I.V.: Automated semantic analysis of schematic data. World Wide Web 11, 427–464 (2008)CrossRefGoogle Scholar
  34. 34.
    Nachira, F., Nicolai, A., Dini, P., Louarn, M.L., Leon, L.R.: Digital Business Ecosystems. European Commission Information Society and Media (2007)Google Scholar
  35. 35.
    Ning, X., Jin, H., Wu, H.: RSS: A framework enabling ranked search on the semantic web. Inf. Process. Manage. 44, 893–909 (2007)CrossRefGoogle Scholar
  36. 36.
  37. 37.
    Patel-Schneider, P., Horrocks, I.: Mapping to RDF graph for OWL.: http://www.w3.org/TR/owl-semantics/mapping.html (2006)
  38. 38.
    Rijsbergan, C.J.v.: Informaiton Retrieval. Butterworths, London, UK (1979)Google Scholar
  39. 39.
    Robertson, S.E., Jones, K.S.: Relevance weighting for search terms. J. Am. Soc. Inf. Sci. 27, 129–146 (1976)CrossRefGoogle Scholar
  40. 40.
    Saha, D., Sahu, S., Shaikh, A.: A Service Platform for OnLine Games. NetGames 2003. ACM, Redwood City (2003) 108–112Google Scholar
  41. 41.
    Salton, G.: The SMART Retrieval System—Experiments in Automatic Document Processing. Prince Hall, Englewood Cliffs (1971)Google Scholar
  42. 42.
    Salton, G., Lesk, M.E.: Computer evaluation of indexing and text processing. J. ACM 15, 8–36 (1968)MATHCrossRefGoogle Scholar
  43. 43.
    Shaikh, A., Sahu, S., Rosu, M., Shea, M., Saha, D.: Implementation of a Service Platform for Online Games. SIGCOMM’04. ACM, Portland (2004) 106–110Google Scholar
  44. 44.
    Shaw, W.M.J., Burgin, R., Howell, P.: Performance standards and evaluations in IR test collections: Cluster-based retrieval models. Inf. Process. Manag. 33, 1–14 (1997)CrossRefGoogle Scholar
  45. 45.
    Su, L.T.: The relevance of recall and precision in user evaluation. J. Am. Soc. Inf. Sci. 45, 207–217 (1999)CrossRefGoogle Scholar
  46. 46.
    W3C: OWL web ontology language overview. http://www.w3.org/TR/owl-features/ (2004)

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Hai Dong
    • 1
  • Farookh Khadeer Hussain
    • 1
  • Elizabeth Chang
    • 1
  1. 1.Digital Ecosystems and Business Intelligence InstituteCurtin University of TechnologyBentleyAustralia

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