Abstract
With the development of cloud computing, more and more web services are deployed on the cloud platform. It provides more solutions to the customers, but accompanies with a critical and fundamental problem, that is, how to easily find the desired web services. Since tags provide meaningful descriptions for web services function and non-function properties, some researchers have employed tags to facilitate web service discovery. However, the existing web service tags are often imprecise and incomplete. To complete the missing tags and correct the noisy ones, an efficient web service Tag Completion and Refinement based on Matrix Completion (TagCRMC) approach is proposed. The TagCRMC approach not only models the low-rank property of service-tag matrix, but also simultaneously integrates the content correlation consistency and the tag correlation consistency to ensure the correct correspondence between web services and tags. Experimental results on the real-world web services collection show the encouraging performance of the TagCRMC approach.
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Acknowledgements
This work is supported by the National Natural Science Foundation (Nos. 61272084, 61201163, 61272422 and 61373137), the National Key Basic Research Development Program (No. 2011CB302903), and the Natural Science Foundation of Jiangsu Province (Nos. BK2011754 and BK20130096), the Key University Natural Science Research Program of Jiangsu (No. 11KJA520002), the Research Fund for the Doctoral Program of High Education (Nos. 20113223110003 and 20093223120001).
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Chen, L., Yang, G., Chen, Z., Xiao, F., Li, X. (2014). Tag Completion and Refinement for Web Service via Low-Rank Matrix Completion. In: Peng, WC., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8643. Springer, Cham. https://doi.org/10.1007/978-3-319-13186-3_26
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DOI: https://doi.org/10.1007/978-3-319-13186-3_26
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