کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6948386 | 1451037 | 2018 | 43 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Time-aware cloud service recommendation using similarity-enhanced collaborative filtering and ARIMA model
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
سیستم های اطلاعاتی
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چکیده انگلیسی
The quality of service (QoS) of cloud services change frequently over time. Existing service recommendation approaches either ignore this property or address it inadequately, leading to ineffective service recommendation. In this paper, we propose a time-aware service recommendation (taSR) approach to address this issue. We first develop a novel similarity-enhanced collaborative filtering (CF) approach to capture the time feature of user similarity and address the data sparsity in the existing PITs (point in time). We then apply autoregressive integrated moving average model (ARIMA) to predict the QoS values in the future PIT under QoS instantaneity. We evaluate the proposed approach and compare it to the state-of-the-art. Our experimental results show that taSR achieves significant performance improvements over existing approaches.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 107, March 2018, Pages 103-115
Journal: Decision Support Systems - Volume 107, March 2018, Pages 103-115
نویسندگان
Shuai Ding, Yeqing Li, Desheng Wu, Youtao Zhang, Shanlin Yang,