research-article

A Spatial-Temporal QoS Prediction Approach for Time-aware Web Service Recommendation

Authors:

Michael R. LyuAuthors Info & Claims

ACM Transactions on the Web (TWEB), Volume 10, Issue 1

Article No.: 7, Pages 1 - 25

https://doi.org/10.1145/2801164

Published: 08 February 2016 Publication History

Abstract

Due to the popularity of service-oriented architectures for various distributed systems, an increasing number of Web services have been deployed all over the world. Recently, Web service recommendation became a hot research topic, one that aims to accurately predict the quality of functional satisfactory services for each end user. Generally, the performance of Web service changes over time due to variations of service status and network conditions. Instead of employing the conventional temporal models, we propose a novel spatial-temporal QoS prediction approach for time-aware Web service recommendation, where a sparse representation is employed to model QoS variations. Specifically, we make a zero-mean Laplace prior distribution assumption on the residuals of the QoS prediction, which corresponds to a Lasso regression problem. To effectively select the nearest neighbor for the sparse representation of temporal QoS values, the geo-location of web service is employed to reduce searching range while improving prediction accuracy. The extensive experimental results demonstrate that the proposed approach outperforms state-of-art methods with more than 10% improvement on the accuracy of temporal QoS prediction for time-aware Web service recommendation.

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Cited By

Wang LChen SZhang XLiu J(2025)Runtime reliability fractional distribution change analytics against cloud-based systems DDoS attacksJournal of Systems and Software10.1016/j.jss.2024.112265220(112265)Online publication date: Feb-2025
https://doi.org/10.1016/j.jss.2024.112265
Jin HZhang PDong HBouguettaya AZomaya A(2024)Swift and Accurate Mobility-Aware QoS Forecasting for Mobile Edge EnvironmentsIEEE Transactions on Services Computing10.1109/TSC.2024.3417339(1-14)Online publication date: 2024
https://doi.org/10.1109/TSC.2024.3417339
Chen MWang RQiao YLuo X(2024)A Generalized Nesterov's Accelerated Gradient-Incorporated Non-Negative Latent-Factorization-of-Tensors Model for Efficient Representation to Dynamic QoS DataIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2024.33603388:3(2386-2400)Online publication date: Jun-2024
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Index Terms

A Spatial-Temporal QoS Prediction Approach for Time-aware Web Service Recommendation
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing systems and tools
2. Information systems
  1. World Wide Web

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Published In

cover image ACM Transactions on the Web

ACM Transactions on the Web Volume 10, Issue 1

February 2016

198 pages

ISSN:1559-1131

EISSN:1559-114X

DOI:10.1145/2870642

Editors:
Brian D. Davison
Lehigh University, USA
,
Marianne Winslett
University of Illinois at Urbana-Champaign

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Copyright © 2016 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 February 2016

Accepted: 01 July 2015

Revised: 01 April 2015

Received: 01 May 2014

Published in TWEB Volume 10, Issue 1

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Funding Sources

National Natural Science Foundation of China
Major State Basic Research Development Program of China (973 Program No. 2015CB352201)
Guangdong Natural Science Foundation
Research Grants Council General Research Fund (CUHK 415113)
National Key Technology R&D Program of the Ministry of Science and Technology of China (No. 2015BAH17F01)

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Cited By

Wang LChen SZhang XLiu J(2025)Runtime reliability fractional distribution change analytics against cloud-based systems DDoS attacksJournal of Systems and Software10.1016/j.jss.2024.112265220(112265)Online publication date: Feb-2025
https://doi.org/10.1016/j.jss.2024.112265
Jin HZhang PDong HBouguettaya AZomaya A(2024)Swift and Accurate Mobility-Aware QoS Forecasting for Mobile Edge EnvironmentsIEEE Transactions on Services Computing10.1109/TSC.2024.3417339(1-14)Online publication date: 2024
https://doi.org/10.1109/TSC.2024.3417339
Chen MWang RQiao YLuo X(2024)A Generalized Nesterov's Accelerated Gradient-Incorporated Non-Negative Latent-Factorization-of-Tensors Model for Efficient Representation to Dynamic QoS DataIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2024.33603388:3(2386-2400)Online publication date: Jun-2024
https://doi.org/10.1109/TETCI.2024.3360338
Cao BWang SXie XPeng QYi YPeng Z(2024)ARIR: an intent recognition-based approach for API recommendationCluster Computing10.1007/s10586-024-04520-527:8(10819-10832)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1007/s10586-024-04520-5
Jawabreh ETaweel A(2024)Qos-based web service selection using time-aware collaborative filtering: a literature reviewComputing10.1007/s00607-024-01283-0106:6(2033-2058)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s00607-024-01283-0
Mao CChen JTowey DZhao ZWen L(2024)QoS prediction of cloud services by selective ensemble learning on prefilling‐based matrix factorizationsConcurrency and Computation: Practice and Experience10.1002/cpe.8282Online publication date: 14-Sep-2024
https://doi.org/10.1002/cpe.8282
Lenka SPradhan SNayak SNayak S(2023)Exploiting Predictability of Random Vector Functional Link Networks in Forecasting Quality of Service (QoS) Parameters of IoT-Based Web Services DataInternational Journal of Sensors, Wireless Communications and Control10.2174/221032791366623041112534713:2(57-70)Online publication date: Apr-2023
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Yin YDi QWan JLiang T(2023)Time-Aware Smart City Services Based on QoS Prediction: A Contrastive Learning ApproachIEEE Internet of Things Journal10.1109/JIOT.2023.328186910:21(18745-18753)Online publication date: 1-Nov-2023
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Yu TYu DWang DHu X(2023)Web service recommendation for mashup creation based on graph networkThe Journal of Supercomputing10.1007/s11227-022-05011-379:8(8993-9020)Online publication date: 1-May-2023
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Boulakbech MMessai NSam YDevogele T(2023)Deep Learning Model for Personalized Web Service Recommendations Using Attention MechanismService-Oriented Computing10.1007/978-3-031-48421-6_2(19-33)Online publication date: 28-Nov-2023
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