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From a Web Services Catalog to a Linked Ecosystem of Services

  • Fatma Slaimi
  • Sana Sellami
  • Omar Boucelma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10546)

Abstract

In this paper, we present a Linked ecosystem of Web services where both Web services, mashups and users are represented as a multigraph structure. For illustration and experimental purposes, a graph has been constructed, in gathering web services metadata from ProgrammableWeb. The graph is stored in a Neo4j graph database and serves as a repository for a realistic collection of web services for achieving services/mashups discovery and recommendation.

Keywords

Web services Discovery Recommendation Linked data Graph databases Neo4j 

References

  1. 1.
    Berry, M.W., Drmac, Z., Jessup, E.R.: Matrices, vector spaces, and information retrieval. SIAM Rev. 41, 335–362 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Bianchini, D., De Antonellis, V., Melchiori, M.: Link-based viewing of multiple web API repositories. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds.) DEXA 2014. LNCS, vol. 8644, pp. 362–376. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-10073-9_30 Google Scholar
  3. 3.
    Liang, T., Chen, L., Wu, J., Bouguettaya, A.: Exploiting heterogeneous information for tag recommendation in API management. In: IEEE International Conference on Web Services, ICWS 2016, pp. 436–443 (2016)Google Scholar
  4. 4.
    Chen, W., Paik, I., Hung, P.C.: Constructing a global social service network for better quality of web service discovery. IEEE Trans. Serv. Comput. 8, 284–298 (2015)CrossRefGoogle Scholar
  5. 5.
    Chen, W., Paik, I.: Improving efficiency of service discovery using Linked databased service publication. Inf. Syst. Front. 15(4), 613–625 (2013)CrossRefGoogle Scholar
  6. 6.
    Lyu, S., Liu, J., Tang, M., Kang, G., Cao, B., Duan, Y.: Three-level views of the web service network: an empirical study based on ProgrammableWeb. In: IEEE International Congress on Big Data (BigData Congress 2014), pp. 374–381 (2014)Google Scholar
  7. 7.
    Deng, S., Huang, L., Yin, Y., Tang, W.: Trust-based service recommendation in social network. Appl. Math. 9, 1567–1574 (2015)Google Scholar
  8. 8.
    Deng, S., Huang, L., Xu, G.: Social network-based service recommendation with trust enhancement. Expert Syst. Appl. 4, 8075–8084 (2014)CrossRefGoogle Scholar
  9. 9.
    Liang, T., Chen, L., Wu, J., Dong, H., Bouguettaya, A.: Meta-path based service recommendation in heterogeneous information networks. In: Sheng, Q.Z., Stroulia, E., Tata, S., Bhiri, S. (eds.) ICSOC 2016. LNCS, vol. 9936, pp. 371–386. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-46295-0_23 CrossRefGoogle Scholar
  10. 10.
    Guo, G., Zhang, J., Yorke-Smith, N.: TrustSVD: collaborative filtering with both the explicit and implicit influence of user trust and of item ratings. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pp. 123–129 (2015)Google Scholar
  11. 11.
    Aljalbout, S., Boucelma, O., Sellami, S.: Modeling and retrieving linked RESTful APIs: a graph database approach. In: Debruyne, C., Panetto, H., Meersman, R., Dillon, T., Weichhart, G., An, Y., Ardagna, C.A. (eds.) OTM 2015. LNCS, vol. 9415, pp. 443–450. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-26148-5_29 Google Scholar
  12. 12.
    Maamar, Z., Wives, L.K., Badr, Y., Elnaffar, S., Boukadi, K., Faci, N.: Linkedws: a novel web services discovery model based on the metaphor of Social networks. Simul. Model. Pract. Theory 19, 121–132 (2011)CrossRefGoogle Scholar
  13. 13.
    Jackson, D.A., Somers, K.M., Harvey, H.H.: Similarity coefficients: measures of co-occurrence and association or simply measures of occurrence? Am. Nat. 133(3), 436–453 (1989)CrossRefGoogle Scholar
  14. 14.
    Bobadilla, J., Ortega, F., Hernando, A., Gutiérrez, A.: Recommender systems survey. Knowl. Based Syst. 46, 109–132 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Aix Marseille Université, CNRS, ENSAM, Université de Toulon, LSIS UMR 7296MarseilleFrance

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