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Neural Computing and Applications

Erschienen in:

01.01.2015 | Original Article

Correlation consistency constrained matrix completion for web service tag refinement

verfasst von: Lei Chen, Geng Yang, Zhengyu Chen, Fu Xiao, Jianyue Shi

Erschienen in: Neural Computing and Applications | Ausgabe 1/2015

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Abstract

With the permeation of web 2.0, large-scale web services with tags are easily available on websites. However, the noisy and incomplete correspondence between web services and tags impedes the tag related web service applications. To address this challenge, a Matrix Completion based Web Service Tag Refinement (MCWSTR) framework is proposed. Firstly, the MCWSTR framework naturally formulates the web service tag refinement problem as a Correlation Consistency Constrained Matrix Completion (C3MC) problem, which jointly model content correlation consistency and tag correlation consistency among web services and tags. Secondly, the MCWSTR framework employs an efficient Fixed Point Iterative algorithm based on Operator Splitting technique to solve the C3MC problem, Experimental results on the real-world web services collection show the encouraging performance of our proposed MCWSTR framework.

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Titel: Correlation consistency constrained matrix completion for web service tag refinement
verfasst von: Lei Chen
Geng Yang
Zhengyu Chen
Fu Xiao
Jianyue Shi
Publikationsdatum: 01.01.2015
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 1/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-014-1704-z

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