A Feedback-corrected Collaborative Filtering for Personalized Real-world Service Recommendation
Keywords:
Internet of Things, service recommendation, similarity measurement, collaborative filteringAbstract
The emergence of Internet of Things (IoT) integrates the cyberspace
with the physical space. With the rapid development of IoT, large amounts of IoT
services are provided by various IoT middleware solutions. So, discovery and selecting
the adequate services becomes a time-consuming and challenging task. This paper
proposes a novel similarity-measurement for computing the similarity between services
and introduces a new personalized recommendation approach for real-world service
based on collaborative filtering. In order to evaluate the performance of proposed
recommendation approach, large-scale of experiments are conducted, which involves
the QoS-records of 339 users and 5825 real web-services. The experiments results
indicate that the proposed approach outperforms other compared approaches in terms
of accuracy and stability.
References
Gustafaason, J. (2011); Integration of wireless sensor and actuator nodes with IT infrastructure using service-oriented architecture, IEEE Trans Industrial Informatics, ISSN 1551-3203, 6(1): 1-10.
Guinard, D.; Trifa, V. (2010); Interacting with the SOA-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services, IEEE Trans Services Computing, ISSN 1939-1374, 3(3): 223-235.
ICT FP7 OPEN IoT Project. Open source solution for the internet of things into the cloud, (2011). http://vmusm03.deri.ie/.
EPFL GSN project (2009). http://sourceforge.net/apps/trac/gsn/.
Cosm. Cosm platform, (2007). https://cosm.com/.
Perera, C.; Zaslavsky, A.; Christen, P. (2013). Context-aware sensor search, selection and ranking model for internet of things middleware. 14th IEEE International Conference on Mobile Data Management, 314-322. http://dx.doi.org/10.1109/MDM.2013.46
Sreenath, R.M.; Singh, M.P. (2003); Agent-based service selection, J Web Semantics, ISSN 1570-8268, 1(3): 261-279.
Zhang, L.J.; Zhang, J.; Cai, H. (2007) Services computing, Springer and Tsinghua University Press, ISSN 0895-4852.
Moser, O.; Rosenberg, F.; Dustdar, S. (2008). Non-intrusive monitoring and service adaptation for ws-bpel, 17th Intl Conf. on World Wide Web, 815-824.
Papazoglou, M; Georgakopoulos, D. (2003). Service-oriented computing, Communications of the ACM, ISSN 0001-0782, 46(10): 25-28.
Zheng, Z.; Ma, H.; Lyu, M.R.; King, I. (2009). Wsrec: A collaborative filtering based web service recommender system, 7th Intl Conf. Web Services, 437-444.
Resnick, P.; Iacovou, N.; Suchak, M.; Bergstrom, P.; Riedl, J. (1994). Grouplens: An open architecture for collaborative filtering of net news, ACM Conf. Computer Supported Cooperative Work, 175-186.
Shardanand, U.; Maes, P. (1995). Social information filtering: Algorithms for automating word of mouth, SIGCHI Conf. Human Factors in Computing Systems, 210-217.
Sarwar, B.; Karypis, G.; Konstan, J.; Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms, 10th Intl Conf. World Wide Web, 285-295.
Breese, J.; Heckerman, D.; Kadie, C. (1998). Empirical analysis of predictive algorithms for collaborative filtering, 14th Intl Conf. on Uncertainty in artificial intelligence, 43-52.
Adomavicius, G.; Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions, IEEE Trans on Knowledge and Data Engineering, ISSN: 1041-4347, 17: 734-749.
Chen, X.; Zheng, Z.; Liu, X.; Huang, Z.; Sun, H. (2013). Personalized qos-aware web service recommendation and visualization, IEEE Trans on Service Computing, ISSN: 1939-1374, 6(1):35-47.
Karta, K. (2005). An investigation on personalized collaborative filtering for web service selection. Honours Programme thesis, University of Western Australia.
Shao, L.S.; et al. (2007). Personalized qos prediction forweb services via collaborative filtering. Intl Conf. on Web Services, 439-446. http://dx.doi.org/10.1109/ICWS.2007.140
Miller, B.; Albert, I.; Lam, S.; Konstan, J.; Riedl, J. (2003). MovieLens unplugged: Experiences with an occasionally connected recommender system. 8th International Conference on Intelligent User Interfaces, 263-266.
Zhao, S.; Zhang, Y.; et al. (2013). A multidimensional resource model for dynamic resource matching in internet of things. Concurrency and Computation: Practice Experience.
http://dx.doi.org/10.1002/cpe.3170
Thio, N.; Karunasekera, S. (2005). Automatic measurement of a qos metric for web service recommendation, Australian Software Engineering Conference, 202-211.
Lipkus, A.H. (1999). A proof of the triangle inequality for the Tanimoto distance, Journal of Mathematical Chemistry, ISSN: 0259-9791, 263-265.
Zheng, Z.; Ma, H.; Lyu, M.R.; King, I. (2011). QoS-aware Web service recommendation by collaborative filtering, IEEE Trans on Service Computing, ISSN: 1939-1374, 4(2): 140-152.
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