کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
392720 665154 2014 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Colbar: A collaborative location-based regularization framework for QoS prediction
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Colbar: A collaborative location-based regularization framework for QoS prediction
چکیده انگلیسی

Quality-of-Service (QoS) is a fundamental element in Service-Oriented Computing (SOC) domain. At the ongoing age of Web 2.0, predicting the missing QoS values becomes more and more important since it is an indispensable preprocess of numerous service-oriented applications. Previous research works on this task underestimate the importance of users’ geographical information, which we argue would contribute to improving prediction accuracy in Web services invocation process. In this paper, we propose a novel collaborative location-based regularization framework (Colbar) to address the problem of personalized QoS prediction. We first leverage the personal geographical and QoS information to identify robust neighborhoods. And then, we collect the wisdom of crowds to construct two location-based regularization terms, which are integrated to build up an unified Matrix Factorization framework. Finally we make intermediate fusions to generate better prediction results. The experimental analysis on a large-scale real-world QoS dataset shows that the prediction accuracy of Colbar outperforms other state-of-the-art approaches in various criteria.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 265, 1 May 2014, Pages 68–84
نویسندگان
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