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2016 | OriginalPaper | Buchkapitel

A Multigraph Approach for Web Services Recommendation

verfasst von : Fatma Slaimi, Sana Sellami, Omar Boucelma, Ahlem Ben Hassine

Erschienen in: On the Move to Meaningful Internet Systems: OTM 2016 Conferences

Verlag: Springer International Publishing

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Abstract

In this paper, we describe a Web services recommendation approach where the services’ ecosystem is represented as a heterogeneous multigraph, and edges may have different semantics. The recommendation process relies on clustering techniques to suggest services “of interest” to a user. Our approach has been implemented as a tool called WesReG (Web services Recommendation with Graphs) on top of Neo4j and its cypher query language. We present the system implementation details and present the results of experiments on a collection of real Web services.

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Vorheriges Kapitel RoSE: Reoccurring Structures Detection in BPMN 2.0 Process Model Collections

Nächstes Kapitel A Generic Framework for Context-Aware Process Performance Analysis

http://www.programmableweb.com/.

http://linkeddata.org/.

http://www.lsis.org/sellamis/Projects.html#WeS-ReG.

http://www.librec.net/.

Berry, M.W., Drmac, Z., Jessup, E.R.: Matrices, vector spaces, and information retrieval. SIAM Rev. 41, 335–362 (1999)MathSciNetCrossRefMATH

Bobadilla, J., Ortega, F., Hernando, A., GutiéRrez, A.: Recommender systems survey. Know. Based Syst. 46, 109–132 (2013)CrossRef

Breese, J.S., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, pp. 43–52. Morgan Kaufmann Publishers Inc. (1998)

Chen, W., Paik, I., Hung, P.C.K.: Constructing a global social service network for better quality of web service discovery. IEEE Trans. Serv. Comput. 8, 284–298 (2015)CrossRef

Chen, Z., Jiang, Y., Zhao, Y.: A collaborative filtering recommendation algorithm based on user interest change and trust evaluation. JDCTA 4, 106–113 (2010)

Choi, K., Yoo, D., Kim, G., Suh, Y.: A hybrid online-product recommendation system: combining implicit rating-based collaborative filtering and sequential pattern analysis. Electron. Commer. Res. Appl. 11, 309–317 (2012)CrossRef

Deng, S., Huang, L., Yin, Y., Tang, W.: Trust-based service recommendation in social network. Appl. Math. 9, 1567–1574 (2015)

Deng, S., Huang, L., Xu, G.: Social network-based service recommendation with trust enhancement. Expert Syst. Appl. 41, 8075–8084 (2014)CrossRef

Golbeck, J., Hendler, J.: Filmtrust: movie recommendations using trust in web-based social networks. In: Proceedings of the IEEE Consumer Communications and Networking Conference, vol. 96, pp. 282–286 (2006)

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)

11.

Heitmann, B., Hayes, C.: Using linked data to build open, collaborative recommender systems. In: AAAI Spring Symposium: Linked Data Meets Artificial Intelligence, pp. 76–81 (2010)

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. Theor. 19, 121–132 (2011)CrossRef

13.

Maaradji, A., Hacid, H., Skraba, R., Lateef, A., Daigremont, J., Crespi, N.: Social-based web services discovery and composition for step-by-step mashup completion. In: IEEE International Conference on Web Services (ICWS 2011), pp. 700–701 (2011)

14.

Mashal, I., Chung, T.-Y., Alsaryrah, O.: Toward service recommendation in internet of things. In: 2015 Seventh International Conference on Ubiquitous and Future Networks (ICUFN), pp. 328–331. IEEE (2015)

15.

Massa, P., Avesani, P.: Trust-aware collaborative filtering for recommender systems. In: Meersman, R. (ed.) CoopIS/DOA/ODBASE 2004. LNCS, vol. 3290, pp. 492–508. Springer, Heidelberg (2004)CrossRef

16.

Slaimi, F., Sellami, S., Boucelma, O., Ben Hassine, A.: Flexible matchmaking for restful web services. In: Meersman, R., et al. (eds.) OTM 2013. LNCS, vol. 8185, pp. 542–554. Springer, Heidelberg (2013)CrossRef

17.

Walter, F.E., Battiston, S., Schweitzer, F.: A model of a trust-based recommendation system on a social network. Auton. Agent. Multi-Agent Syst. 16, 57–74 (2008)CrossRef

18.

Zhang, X., He, K., Wang, J., Wang, C., Tian, G., Liu, J.: Web service recommendation based on watchlist via temporal and tag preference fusion. In: 2014 IEEE International Conference on Web Services (ICWS), pp. 281–288. IEEE (2014)

19.

Kim, C., Kim, J.: A recommendation algorithm using multi-level association rules. In: IEEE/WIC International Conference on Web Intelligence (WI 2003), pp. 524–527 (2003)

20.

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, Roland R. (eds.) DEXA 2014, Part I. LNCS, vol. 8644, pp. 362–376. Springer, Heidelberg (2014)

21.

Zheng, Z.B., Ma, H., Lyu, M.R., King, I.: QoS-aware web service recommendation by collaborative filtering. IEEE Trans. Serv. Comput. 4, 140–152 (2011)CrossRef

22.

Cao, J., Wu, Z., Wang, Y., Zhuang, Y.: Hybrid collaborative filtering algorithm for bidirectional Web service recommendation. Knowl. Inf. Syst. 36(3), 607–627 (2013)

23.

Manikrao, U.S., Prabhakar, T.V.: Dynamic selection of web services with recommendation system. In: International Conference on Next Generation Web Services Practices (NWeSP 2005) (2005)

Titel: A Multigraph Approach for Web Services Recommendation
verfasst von: Fatma Slaimi
Sana Sellami
Omar Boucelma
Ahlem Ben Hassine
Verlag: Springer International Publishing
Buch: On the Move to Meaningful Internet Systems: OTM 2016 Conferences
Print ISBN: 978-3-319-48471-6

Electronic ISBN: 978-3-319-48472-3

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-48472-3_16

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