Discovering composable web services using functional semantics and service dependencies based on natural language requests

Abstract

The processes of service discovery, selection and composition are crucial tasks in web service based application development. Most web service-driven applications are complex and are composed of more than one service, so, it becomes important for application designers to identify the best service to perform the next task in the intended application’s workflow. In this paper, a framework for discovering composable service sets as per user’s complex requirements is proposed. The proposed approach uses natural language processing and semantics based techniques to extract the functional semantics of the service dataset and also to understand user context. In case of simple queries, basic services may be enough to satisfy the user request, however, in case of complex queries, several basic services may have to be identified to serve all the requirements, in the correct sequence. For this, the service dependencies of all the services are used for constructing a service interface graph for finding suitable composable services. Experiments showed that the proposed approach was effective towards finding relevant services for simple & complex queries and achieved an average accuracy rate of 75.09 % in finding correct composable service templates.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Notes

  1. 1.

    OWL-S Service Retrieval Test Collection version 4, Available online http://projects.semwebcentral.org/projects/owls-tc/

References

  1. Akkiraju, R., Srivastava, B., Ivan, A., Goodwin, R., & Syeda-Mahmood, T. (2006). Semantic matching to achieve web service discovery and composition, E-Commerce Technology, 2006. The 8th IEEE International Conference on and Enterprise Computing, E-Commerce, and E-Services (pp. 70–70).

  2. Almasri, E., & Mahmoud, Q.H. (2009). A broker for universal access to web services, Communication Networks and Services Research Conference, 2009. CNSR’09. Seventh Annual (pp. 118–125).

    Google Scholar 

  3. Benatallah, B., Hacid, M.S., Leger, A., Rey, C., & Toumani, F. (2005). On automating web services discovery. VLDB J., 14(1), 84– 96.

    Article  Google Scholar 

  4. Bianchini, D., Garza, P., & Quintarelli, E. (2015). Characterization and search of web services through intensional knowledge. Journal of Intelligent Information Systems pp 1–27.

  5. Brogi, A., Corfini, S., & Popescu, R. (2005). Composition-oriented service discovery, Software Composition (pp. 15–30): Springer.

  6. Chan, N.N., Gaaloul, W., & Tata, S. (2011). A web service recommender system using vector space model and latent semantic indexing. In 2011 IEEE International Conference on Advanced Information Networking and Applications (AINA) (pp. 602– 609).

  7. Cuzzocrea, A., & Fisichella, M. (2011). Discovering semantic web services via advanced graph-based matching. In IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2011 (pp. 608–615).

  8. Della-Valle, E., Cerizza, D., Celino, I., Turati, A., Lausen, H., Steinmetz, N., Erdmann, M., & Funk, A. (2008). Realizing service-finder: Web service discovery at web scale. In European Semantic Technology Conference (ESTC), Vienna.

  9. D’Mello, D., Ananthanarayana, V., & Santhi, T. (2008). A qos broker based architecture for dynamic web service selection. In Modeling & Simulation, 2008. AICMS 08. Second Asia International Conference on (pp. 101–106).

  10. Dong, X., Halevy, A., Madhavan, J., Nemes, E., & Zhang, J. (2004). Similarity search for web services. In Proceedings of the Thirtieth international conference on Very large data bases-Volume 30, VLDB Endowment (pp. 372–383).

  11. Elgazzar, K., & et al. (2010). Clustering WSDL documents to bootstrap the discovery of web services. In IEEE Intl Conf on Web Services (ICWS), IEEE.

  12. Fang, L., Wang, L., Li, M., Zhao, J., Zou, Y., & Shao, L. (2012). Towards automatic tagging for web services. In 2012 IEEE 19th International Conference on Web Services (ICWS) (pp. 528–535).

  13. Feng, Z., Peng, R., Wong, R.K., He, K., Wang, J., Hu, S., & Li, B. (2013). Qos-aware and multi-granularity service composition. Infor. Syst. Front., 15(4), 553–567.

    Article  Google Scholar 

  14. Fethallah, H., & Chikh, A. (2013a). Automated retrieval of semantic web services: a matching based on conceptual indexation. Int. Arab. J. Inf. Technol., 10(1), 61–66.

    Google Scholar 

  15. Fethallah, H., & Chikh, A. (2013b). Automated retrieval of semantic web services: a matching based on conceptual indexation. Int. Arab. J. Inf. Technol., 10(1), 61–66.

    Google Scholar 

  16. Hamadi, R., & Benatallah, B. (2003). A petri net-based model for web service composition. In Proceedings of the 14th Australasian database conference-Volume, (Vol. 17 pp. 191–200): Australian Computer Society, Inc.

  17. Hao, Y., Zhang, Y., & Cao, J. (2010). Web services discovery and rank: An information retrieval approach. Futur. Gener. Comput. Syst., 26(8), 1053–1062.

    Article  Google Scholar 

  18. Hashemian, S., & Mavaddat, F. (2005). A graph-based approach to web services composition. In The 2005 Symposium on Applications and the Internet, 2005. Proceedings. doi:10.1109/SAINT.2005.4 (pp. 183–189).

  19. Jiang, J.J., & Conrath, D.W. (1997). Semantic similarity based on corpus statistics and lexical taxonomy. arXiv:cmp-lg/9709008.

  20. Klusch, M., Fries, B., & Sycara, K. (2006). Automated semantic web service discovery with owls-mx. In Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (pp. 915–922).

  21. Kuang, L., Li, Y., Deng, S., & Wu, Z. (2007). Inverted indexing for composition-oriented service discovery. In IEEE International Conference on Web Services, 2007. ICWS 2007. (pp. 257– 264).

  22. Li, S., Huang, S.M., Yen, D.C., & Sun, J.C. (2013). Semantic-based transaction model for web service. Inf. Syst. Front., 15(2), 249–268.

    Article  Google Scholar 

  23. Li, Y., Xiong, J., Liu, X., Zhang, H., & Zhang, P. (2014). Folksonomy-based in-depth annotation of web services. In 2014 IEEE 8th International Symposium on Service Oriented System Engineering (SOSE) (pp. 243–249).

  24. Liang, Q.A., & Su, S.Y. (2005). AND/OR graph and search algorithm for discovering composite web services. Int. J. Web. Ser. Res. (IJWSR), 2(4), 48–67.

    Article  Google Scholar 

  25. Lin, M., & Cheung, D.W. (2014). Automatic tagging web services using machine learning techniques. In Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)-Volume 02 (pp. 258–265).

  26. Ma, J., Zhang, Y., & He, J. (2008). Web services discovery based on latent semantic approach. In IEEE International Conference on Web Services, 2008. ICWS’08. (pp. 740–747).

  27. Nayak, R., & Lee, B. (2007). Web service discovery with additional semantics and clustering.

  28. Oh, S.C., On, B.W., Larson, E., & Lee, D. (2005). Bf*: Web services discovery and composition as graph search problem. In The 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service, 2005. EEE ’05. Proceedings (pp. 784–786). doi:10.1109/EEE.2005.41.

  29. Pedrinaci, C., Liu, D., Maleshkova, M., Lambert, D., Kopecky, J., & Domingue, J. (2010). iserve: a linked services publishing platform. In CEUR workshop proceedings, Vol. 596.

  30. Peng, Y., & Wu, C. (2010). Automatic semantic web service discovery based on assignment algorithm. In 2010 2nd International Conference on Computer Engineering and Technology, Vol. 6.

  31. Platzer, C., & Dustdar, S. (2005). A vector space search engine for web services. Third European Conference on Web Services DOI 0-7695-2484-2/05.

  32. Rong, W., Peng, B., Ouyang, Y., Liu, K., & Xiong, Z. (2015). Collaborative personal profiling for web service ranking and recommendation. Inf. Syst. Front., 17(6), 1265–1282.

    Article  Google Scholar 

  33. Sangers, J., Frasincar, F., Hogenboom, F., & Chepegin, V. (2013). Semantic web service discovery using natural language processing techniques. Expert Syst. Appl., 40(11), 4660–4671.

    Article  Google Scholar 

  34. Shiaa, M.M., Fladmark, J.O., & Thiell, B. (2008). An incremental graph-based approach to automatic service composition. In IEEE International Conference on Services Computing, 2008. SCC’08. (Vol. 1 pp. 397–404).

  35. Song, H., Cheng, D., Messer, A., & Kalasapur, S. (2007). Web service discovery using general-purpose search engines. In IEEE International Conference on Web Services, 2007. ICWS 2007. (pp. 265–271).

  36. Steinmetz, N., Lausen, H., & Brunner, M. (2009). Web service search on large scale. In Service-Oriented Computing (pp. 437–444): Springer.

  37. Truong, H.L., & Dustdar, S. (2009). A survey on context aware web service systems. Int. J. Web Infor. Syst., 5(1), 5–31. doi:10.1108/17440080910947295.

    Article  Google Scholar 

  38. Varguez-Moo, M., Moo-Mena, F., & Uc-Cetina, V. (2013). Use of classification algorithms for semantic web services discovery. J. Comput., 8(7), 1810–1814.

    Article  Google Scholar 

  39. Wohed, P., van der Aalst, W.M., Dumas, M., & Ter Hofstede, A.H. (2003). Analysis of web services composition languages: The case of bpel4ws. In Conceptual Modeling-ER 2003 (pp. 200–215): Springer.

  40. Wu, C., & Chang, E. (2008). Searching services on the web- a public web services discovery approach. In Third Conf. on Signal-Image Technologies and Internet based Systems, IEEE.

  41. Wu, C., & et al. (2008). An empirical approach for semantic web services discovery. In 19th Australian Conference on Software Engineering, 2008. ASWEC 2008. (pp. 412–421).

  42. Xie, X., Chen, K., & Li, J. (2006). A composition oriented and graph-based service search method. In The Semantic Web–ASWC 2006 (pp. 530–536): Springer.

  43. Yang, J., & Zhou, X. (2014). Semi-automatic algorithm based on web service classification. In Advanced Science and Technology Letters, (Vol. 53 pp. 88–91).

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Sowmya Kamath S.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

S, S.K., V. S., A. Discovering composable web services using functional semantics and service dependencies based on natural language requests. Inf Syst Front 21, 175–189 (2019). https://doi.org/10.1007/s10796-017-9738-2

Download citation

Keywords

  • Web service discovery
  • Service composition
  • Natural language processing
  • Semantics