Abstract
A vast number of business services have been published on the Web in an attempt to achieve cost reductions and satisfy user demand. Service retrieval consequently plays an important role, but unfortunately existing research focuses on crisp service retrieval techniques which are unsuitable for vague real world information. In this paper, we propose a new fuzzy service retrieval approach which consists of two modules: service annotation and service retrieval. Related service concepts for a given query are semantically retrieved, following which services that are annotated to those concepts are retrieved. The degree of retrieval of the retrieval module and the similarity between a service, a concept, and a query are fuzzy. Our experiment shows that the proposed approach performs better than a non-fuzzy approach on Recall measure.
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Stavropoulos, T.G., Vrakas, D., Vlahavas, I.: Iridescent: A tool for rapid semantic annotation of web service descriptions. In: Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics, Madrid, Spain, pp. 1–9. ACM (2013)
Scicluna, J., Blank, C., Steinmetz, N., Simperl, E.: Crowd Sourcing Web Service Annotations. In: 2012 AAAI Spring Symposium Series (2012)
Patil, A.A., Oundhakar, S.A., Sheth, A.P., Verma, K.: Meteor-s web service annotation framework. In: Proceedings of the 13th International Conference on World Wide Web, pp. 553–562. ACM, New York (2004)
Hui, W., Zhiyong, F., Shizhan, C., Jinna, X., Yang, S.: Constructing Service Network via Classification and Annotation. In: 2010 Fifth IEEE International Symposium on Service Oriented System Engineering (SOSE), pp. 69–73 (2010)
Bo, J., Zhiyuan, L.: A New Algorithm for Semantic Web Service Matching. Journal of Software (1796217X) 8, 351–356 (2013)
Meyer, H., Weske, M.: Light-Weight Semantic Service Annotations Through Tagging. In: Dan, A., Lamersdorf, W. (eds.) ICSOC 2006. LNCS, vol. 4294, pp. 465–470. Springer, Heidelberg (2006)
Zhai, J., Cao, Y., Chen, Y.: Semantic information retrieval based on fuzzy ontology for intelligent transportation systems. In: IEEE International Conference on Systems, Man and Cybernetics, SMC 2008, pp. 2321–2326. IEEE (2008)
Dong, H., Hussain, F.K., Chang, E.: A service search engine for the industrial digital ecosystems. IEEE Transactions on Industrial Electronics 58, 2183–2196 (2011)
de Castilho, R.E., Gurevych, I.: Semantic Service Retrieval Based on Natural Language Querying and Semantic Similarity. In: ICSC, pp. 173–176 (2011)
Madkour, M., Maach, A., Driss, E., Hasbi, A.: Fuzzy-based approach for context-aware service retrieval. In: 2012 Second International Conference on Innovative Computing Technology (INTECH), pp. 396–401 (2012)
Zhao, W., Peng, L., Zhang, J., Tian, C.: A fuzzy service matching algorithm based on Bloom filter. In: 2012 IEEE 14th International Conference on Communication Technology (ICCT), pp. 945–950. IEEE (2012)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley Longman, Boston (1999)
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Chotipant, S., Hussain, F.K., Dong, H., Hussain, O.K. (2014). A Fuzzy VSM-Based Approach for Semantic Service Retrieval. In: Loo, C.K., Yap, K.S., Wong, K.W., Beng Jin, A.T., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8836. Springer, Cham. https://doi.org/10.1007/978-3-319-12643-2_82
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DOI: https://doi.org/10.1007/978-3-319-12643-2_82
Publisher Name: Springer, Cham
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