Abstract
Current approaches for service discovery are based on semantic knowledge, such as ontologies and service behavior (described as process model). However, these approaches still remain with a high selectivity rate, resulting in a large number of services offering similar functionalities and behavior. One way to improve the selectivity rate and to provide the best suited services is to cope with user preferences defined on quality attributes. In this paper, we propose and evaluate a novel approach for service retrieval that takes into account the service process model and relies both on preference satisfiability and structural similarity. User query and target process models are represented as annotated graphs, where user preferences on QoS attributes are modelled by means of fuzzy sets. A flexible evaluation strategy based on fuzzy linguistic quantifiers (such as almost all) is introduced. Then, two families of ranking methods are discussed. Finally, an extensive set of experiments based on real data sets is conducted, on one hand, to demonstrate the efficiency and the scalability of our approach, and on the other hand, to analyze the effectiveness and the accuracy of the proposed ranking methods compared to expert evaluation.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Klusch, M., Fries, B., Sycara, K.: Automated semantic web service discovery with owls-mx. In: Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, ser. AAMAS 2006, pp. 915–922 (2006)
Dijkman, R., Dumas, M., García-Bañuelos, L.: Graph matching algorithms for business process model similarity search. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 48–63. Springer, Heidelberg (2009)
van Dongen, B., Dijkman, R., Mendling, J.: Measuring similarity between business process models. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 450–464. Springer, Heidelberg (2008)
Grigori, D., Corrales, J.C., Bouzeghoub, M., Gater, A.: Ranking bpel processes for service discovery. IEEE Transactions on Services Computing 3, 178–192 (2010)
Şora, I., Lazăr, G., Lung, S.: Mapping a fuzzy logic approach for qos-aware service selection on current web service standards. In: ICCC-CONTI, pp. 553–558 (2010)
Zhang, Y., Huang, H., Yang, D., Zhang, H., Chao, H.-C., Huang, Y.-M.: Bring qos to p2p-based semantic service discovery for the universal network. Personal Ubiquitous Computing 13(7), 471–477 (2009)
Kritikos, K., Plexousakis, D.: Semantic qos metric matching. In: Proc. of ECOWS, pp. 265–274 (2006)
Dubois, D., Prade, H.: Using fuzzy sets in flexible querying: Why and how? In: Proc. of FQAS, pp. 89–103 (1996)
Lemos, F., Gater, A., Grigori, D., Bouzeghoub, M.: Adding preferences to semantic process model matchmaking. In: Proc. of GAOC (2011)
Hristidis, V., Koudas, N., Papakonstantinou, Y.: Prefer: A system for the efficient execution of multi-parametric ranked queries. In: SIGMOD Conference, pp. 259–270 (2001)
Bosc, P., Pivert, O.: Sqlf: a relational database language for fuzzy querying. IEEE Trans. on Fuzzy Systems 3(1), 1–17 (1995)
Chomicki, J.: Preference formulas in relational queries. ACM Transactions on Database Systems 28(4), 427–466 (2003)
Kießling, W.: Foundations of preferences in database systems. In: VLDB. VLDB Endowment, pp. 311–322 (2002)
Börzsönyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: ICDE, pp. 421–430 (2001)
Zadeh, L.A.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)
D’Mello, D.A., Kaur, I., Ram, N., Ananthanarayana, V.S.: Semantic web service selection based on business offering. In: Proc. of EMS, pp. 476–481 (2008)
Agarwal, S., Lamparter, S., Studer, R.: Making Web services tradable: A policy-based approach for specifying preferences on Web service properties. Web Semantics: Science, Services and Agents on The World Wide Web 7(1), 11–20 (2009)
Sathya, M., Swarnamugi, M., Dhavachelvan, P., Sureshkumar, G.: Evaluation of qos based web- service selection techniques for service composition. IJSE 1, 73–90 (2010)
Lin, M., Xie, J., Guo, H., Wang, H.: Solving qos-driven web service dynamic composition as fuzzy constraint satisfaction. In: Proc. of EEE, pp. 9–14 (2005)
Chen, M.-F., Gwo-Hshiung, T., Ding, C.: Fuzzy mcdm approach to select service provider. In: Proc. of ICFS (2003)
Xiong, P., Fanin, Y.: Qos-aware web service selection by a synthetic weight. In: Proc. of FSKD (3), pp. 632–637 (2007)
Hafeez, O., Chung, S., Cock, M.D., Davalos, S.: Towards an intelligent service broker with imprecise constraints: Fuzzy logic based service selection by using sawsdl. TCSS 702 Design Project in Computing and Software Systems, University of Washington (2008)
Dumas, M., García-Bañuelos, L., Polyvyanyy, A., Yang, Y., Zhang, L.: Aggregate quality of service computation for composite services. In: Maglio, P.P., Weske, M., Yang, J., Fantinato, M. (eds.) ICSOC 2010. LNCS, vol. 6470, pp. 213–227. Springer, Heidelberg (2010)
Wu, Z., Palmer, M.S.: Verb semantics and lexical selection. In: Proc. of ACL, pp. 133–138 (1994)
Ehrig, M., Koschmider, A., Oberweis, A.: Measuring similarity between semantic business process models. In: Proc. of the Fourth APCCM, vol. 67, pp. 71–80 (2007)
Koschmider, A., Oberweis, A.: How to detect semantic business process model variants? In: Proc. of the 2007 ACM SAC, pp. 1263–1264 (2007)
Glöckner, I.: Fuzzy Quantifiers in Natural Language: Semantics and Computational Models. Der Andere Verlag, Osnabrück (2004)
Yager, R.R.: General multiple-objective decision functions and linguistically quantified statements. International Journal of Man-Machine Studies 21, 389–400 (1984)
Liétard, L.: A new definition for linguistic summaries of data. In: IEEE World Congress on Computational Intelligence, Fuzzy. IEEE, Hong-Kong (2008)
Dubois, D., Prade, H.: Handling bipolar queries in fuzzy information processing. In: Galindo, J. (ed.) Handbook of Research on Fuzzy Information Processing in Databases. IGI Global, pp. 97–114 (2008)
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
Abbaci, K. et al. (2011). Selecting and Ranking Business Processes with Preferences: An Approach Based on Fuzzy Sets. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2011. OTM 2011. Lecture Notes in Computer Science, vol 7044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25109-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-25109-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25108-5
Online ISBN: 978-3-642-25109-2
eBook Packages: Computer ScienceComputer Science (R0)