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Personalized decision-strategy based web service selection using a learning-to-rank algorithm


Saleem, MS and Ding, C and Liu, X and Chi, C, Personalized decision-strategy based web service selection using a learning-to-rank algorithm, IEEE Transactions on Services Computing, 8, (5) pp. 727-739. ISSN 1939-1374 (2015) [Non Refereed Article]

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DOI: doi:10.1109/TSC.2014.2377724


In order to choose from a list of functionally similar services, users often need to make their decisions based on multiple QoS criteria they require on the target service. In this process, different users may follow different decision making strategies, some are compensatory in which only an overall value on all the criteria is evaluated, some evaluate one criterion at a time in the order of their importance levels, while others count on the number of winning criteria. Most of the current QoS-based service selection systems do not consider these decision strategies in the ranking process, which we believe are crucial for generating accurate ranking results for individual users. In this paper, we propose a decision strategy based service ranking model. Furthermore, considering that different users follow different strategies in different contexts at different times, we apply a machine learning algorithm to learn a personalized ranking model for individual users based on how they select services in the past. We have implemented and tested the proposed approach, and our experiment results show the effectiveness of the approach.

Item Details

Item Type:Non Refereed Article
Keywords:web service selection, quality of service, QoS, decision strategy, learning to rank
Research Division:Information and Computing Sciences
Research Group:Distributed computing and systems software
Research Field:Service oriented computing
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the information and computing sciences
UTAS Author:Chi, C (Dr Chi-Hung Chi)
ID Code:117305
Year Published:2015
Web of Science® Times Cited:10
Deposited By:Information and Communication Technology
Deposited On:2017-06-07
Last Modified:2017-06-07

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