Abstract
A Web service is a software functionality accessible through the network. Web services are intended to be composed into coarser-grained applications. Achieving a required composite functionality requires the discovery of a collection of Web services out of the enormous service space. Each service must be examined to verify its provided functionality, making the selection task neither efficient nor practical. Moreover, when a service in a composition becomes unavailable, the whole composition may become functionally broken. Therefore, an equivalent service must be retrieved to replace the broken one, thus spending more time and effort. In this paper, we propose an approach for Web service classification based on FCA, using their operations estimated similarities. The generated lattices make the identification of candidate substitutes to a given service straightforward. Thus, service compositions can be achieved more easily and with backup services, so as to easily recover the functionality of a broken service.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Web Services Description Language (WSDL) 1.1, http://www.w3.org/TR/wsdl
UDDI Version 3.0.2, http://www.uddi.org/pubs/uddi_v3.htm
Newcomer, E., Lomow, G.: Understanding SOA with Web Services (Independent Technology Guides). Addison-Wesley Professional, Reading (2004)
Ganter, B., Wille, R.: Formal Concept Analysis. Mathematical foundations edn. Springer, Heidelberg (1999)
Godin, R., Mineau, G.W., Missaoui, R.: Méthodes de classification conceptuelle basées sur les treillis de Galois et applications. Revue d’intelligence Artificielle 9, 105–137 (1995)
Carpineto, C., Romano, G.: A lattice conceptual clustering system and its application to browsing retrieval. Machine Learning 24, 95–122 (1996)
The Concept Explorer, http://conexp.sourceforge.net/
Dong, X., Halevy, A., Madhavan, J., Nemes, E., Zhang, J.: Similarity search for web services. In: Proc. of VLDB 2004, VLDB Endowment, pp. 372–383 (2004)
Stroulia, E., Wang, Y.: Structural and semantic matching for assessing web-service similarity. Int. J. Cooperative Inf. Syst. 14, 407–438 (2005)
Kokash, N.: A comparison of web service interface similarity measures. In: Proc. of STAIRS 2006, pp. 220–231. IOS Press, Amsterdam (2006)
Azmeh, Z., Huchard, M., Messai, N., Tibermacine, C., Urtado, C., Vauttier, S.: Many-Valued Concept Lattices for Backing Composite Web Services. Technical Report, LIRMM (2010)
Web Services Business Process Execution Language Version 2.0, http://docs.oasis-open.org/wsbpel/2.0/wsbpel-v2.0.html
NetBeans IDE, http://www.netbeans.org/
Seekda Web Services Search Engine, http://webservices.seekda.com
Service-Finder Web Services Search Engine, http://demo.service-finder.eu
Cohen, W.W., Ravikumar, P.D., Fienberg, S.E.: A comparison of string distance metrics for name-matching tasks. In: Kambhampati, S., Knoblock, C.A. (eds.) IIWeb, pp. 73–78 (2003)
Tilley, T., Cole, R., Becker, P., Eklund, P.: A survey of formal concept analysis support for software engineering activities. In: Ganter, B., Stumme, G., Wille, R. (eds.) Formal Concept Analysis. LNCS (LNAI), vol. 3626, pp. 250–271. Springer, Heidelberg (2005)
Godin, R., Mili, H.: Building and maintaining analysis-level class hierarchies using galois lattices. In: OOPSLA, pp. 394–410 (1993)
Snelting, G., Tip, F.: Understanding class hierarchies using concept analysis. ACM Trans. Program. Lang. Syst. 22, 540–582 (2000)
Huchard, M., Dicky, H., Leblanc, H.: Galois lattice as a framework to specify building class hierarchies algorithms. ITA 34, 521–548 (2000)
Godin, R., Valtchev, P.: Formal concept analysis-based class hierarchy design in object-oriented software development. In: Ganter, B., Stumme, G., Wille, R. (eds.) Formal Concept Analysis. LNCS (LNAI), vol. 3626, pp. 304–323. Springer, Heidelberg (2005)
Aboud, N.A., Arévalo, G., Falleri, J.R., Huchard, M., Tibermacine, C., Urtado, C., Vauttier, S.: Automated architectural component classification using concept lattices. In: Proc. of WICSA/ECSA 2009. IEEE Computer Society Press, Cambridge (2009)
Arévalo, G., Desnos, N., Huchard, M., Urtado, C., Vauttier, S.: FCA-based service classification to dynamically build efficient software component directories. International Journal of General Systems 38, 427–453 (2009)
Liskov, B.: Keynote address - data abstraction and hierarchy. SIGPLAN Not. 23, 17–34 (1987)
Lindig, C.: Concept-based component retrieval. In: Köhler, J., Giunchiglia, F., Green, C., Walther, C. (eds.) Working Notes of the IJCAI 1995 Workshop: Formal Approaches to the Reuse of Plans, Proofs, and Programs, Montréal, Canada, pp. 21–25 (1995)
Fischer, B.: Specification-based browsing of software component libraries. In: Proc. of ASE 1998, Honolulu, USA, pp. 74–83 (1998)
Sigonneau, B., Ridoux, O.: Indexation multiple et automatisée de composants logiciels. Technique et Science Informatiques 25, 9–42 (2006)
Brockmans, S., Erdmann, M., Schoch, W.: Service-finder deliverable d4.1. research report about current state of the art of matchmaking algorithms. Technical report (2008)
Lausen, H., Steinmetz, N.: Survey of current means to discover web services. Technical report, Semantic Technology Institute, STI (2008)
Aversano, L., Bruno, M., Canfora, G., Penta, M.D., Distante, D.: Using concept lattices to support service selection. Int. J. Web Service Res. 3, 32–51 (2006)
Bruno, M., Canfora, G., Penta, M.D., Scognamiglio, R.: An approach to support web service classification and annotation. In: EEE, pp. 138–143. IEEE Computer Society, Los Alamitos (2005)
Peng, D., Huang, S., Wang, X., Zhou, A., et al: Concept-based retrieval of alternate web services. In: Zhou, L.-z., Ooi, B.-C., Meng, X. (eds.) DASFAA 2005. LNCS, vol. 3453, pp. 359–371. Springer, Heidelberg (2005)
Azmeh, Z., Huchard, M., Tibermacine, C., Urtado, C.: SylvainVauttier: Using concept lattices to support web service compositions with backup services. In: Proc. of ICIW 2010, pp. 363–368. IEEE Computer Society, Los Alamitos (2010)
Kaytoue, M., Assaghir, Z., Napoli, A., Kuznetsov, S.O.: Embedding tolerance relations in formal concept analysis: an application in information fusion. In: Huang, J., Koudas, N., Jones, G., Wu, X., Collins-Thompson, K., An, A. (eds.) CIKM, pp. 1689–1692. ACM, New York (2010)
Crasso, M., Zunino, A., Campo, M.: Awsc: An approach to web service classification based on machine learning techniques. Inteligencia Artificial, Revista Iberoamericana de Interligencia Artificial 12(37), 25–36 (2008)
Heß, A., Kushmerick, N.: Learning to attach semantic metadata to web services. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 258–273. Springer, Heidelberg (2003)
Ma, J., Zhang, Y., He, J.: Efficiently finding web services using a clustering semantic approach. In: Proc. of CSSSIA 2008, pp. 1–8. ACM, New York (2008)
Lu, J., Yu, Y.: Web service search: Who, when, what, and how. In: WISE Workshops, pp. 284–295 (2007)
Günay, A., Yolum, P.: Structural and semantic similarity metrics for web service matchmaking. In: Psaila, G., Wagner, R. (eds.) EC-Web 2007. LNCS, vol. 4655, pp. 129–138. Springer, Heidelberg (2007)
Bouillet, E., Feblowitz, M., Feng, H., Liu, Z., Ranganathan, A., Riabov, A.: A folksonomy-based model of web services for discovery and automatic composition. In: IEEE International Conference on Services Computing (SCC), pp. 389–396. IEEE Computer Society, Los Alamitos (2008)
Platzer, C., Dustdar, S.: A vector space search engine for web services. In: Third IEEE European Conference on Web Services, ECOWS 2005, pp. 62–71 (2005)
Wang, Y., Stroulia, E.: Semantic structure matching for assessing web service similarity. In: Orlowska, M.E., Weerawarana, S., Papazoglou, M.P., Yang, J. (eds.) ICSOC 2003. LNCS, vol. 2910, pp. 194–207. Springer, Heidelberg (2003)
Crasso, M., Zunino, A., Campo, M.: Query by example for web services. In: Proc. of SAC 2008, pp. 2376–2380. ACM, New York (2008)
Messai, N., Devignes, M.D., Napoli, A., Smaïl-Tabbone, M.: Using domain knowledge to guide lattice-based complex data exploration. In: Proc. of ECAI 2010, pp. 847–852. IOS Press, Amsterdam (2010)
Huchard, M., Hacene, M.R., Roume, C., Valtchev, P.: Relational concept discovery in structured datasets. Ann. Math. Artif. Intell. 49, 39–76 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Azmeh, Z. et al. (2011). Backing Composite Web Services Using Formal Concept Analysis. In: Valtchev, P., Jäschke, R. (eds) Formal Concept Analysis. ICFCA 2011. Lecture Notes in Computer Science(), vol 6628. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20514-9_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-20514-9_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20513-2
Online ISBN: 978-3-642-20514-9
eBook Packages: Computer ScienceComputer Science (R0)