Journal ArticleDOI
A Classification Based Web Service Selection Approach
Lalit Purohit,Sandeep Kumar +1 more
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TLDR
An improved PROMETHEE method is applied to most eligible web services and Maximizing Deviation Method based hybrid weight evaluation mechanism is adopted and top-k web services matching closely with the QoS requirements of the end user are selected.Abstract:
Selection of an appropriate web service fulfilling the requirements of the end user is a challenging task. Most of the existing systems use Quality of Service (QoS) as predominant parameter for web service selection, without any preprocessing or filtering. These systems consider all of the candidate web services during selection process and require unnecessary processing of those web services which are far below the expectations of the end user. In this work, an approach for web service selection based on QoS parameters is proposed. The proposed method starts with prefiltering of candidate web services using classification technique. An improved PROMETHEE method, we call it as PROMETHEE Plus, is applied to most eligible web services and Maximizing Deviation Method based hybrid weight evaluation mechanism is adopted. Top-k web services matching closely with the QoS requirements of the end user are selected. Experiments on the dataset of real world web services are conducted. Experimental results show that our approach performs better in terms of end user satisfaction and efficiency with reference to the existing similar approaches.read more
Citations
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Journal ArticleDOI
A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction
TL;DR: Zhang et al. as discussed by the authors proposed a posterior-neighborhood-regularized latent factor (PLF) model for QoS prediction, which decomposes the latent factor analysis process into three phases.
Journal Article
Best web service selection based on the decision making between QoS criteria of service
TL;DR: In this article, the authors proposed a best web service selection method which helps to find a service provider providing the optimal quality, which is different from the AHP method in that there's no need to perform a pair-wise comparison again when comparative alternatives are added or deleted.
Proceedings ArticleDOI
Clustering Based Approach for Web Service Selection Using Skyline Computations
Lalit Purohit,Sandeep Kumar +1 more
TL;DR: The clustering is applied to candidate web services to determine similar services on the basis of QoS information and it is evident from the results of experimentation that the proposed approach is better than existing similar approaches for web service selection.
Journal ArticleDOI
Trustworthiness prediction of cloud services based on selective neural network ensemble learning
TL;DR: Selective ensemble learning is introduced to address the trust problem for cloud services and shows that the proposed algorithms are not only better than the basic BPNN method in prediction precision, but also outperform current state-of-the-art trust prediction algorithms.
Proceedings ArticleDOI
A Hybrid MCDM Framework for Efficient Web Services Selection Based on QoS
TL;DR: An efficient framework to handle the large number of candidates, Skyline method, and weighting QoS attributes is proposed, which can better elicitate the user preferences and retrieve the best ranked K-Representative Skyline Web Services.
References
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Journal ArticleDOI
On combining classifiers
TL;DR: A common theoretical framework for combining classifiers which use distinct pattern representations is developed and it is shown that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision.
Proceedings ArticleDOI
The Skyline operator
TL;DR: This work shows how SSL can be extended to pose Skyline queries, present and evaluate alternative algorithms to implement the Skyline operation, and shows how this operation can be combined with other database operations, e.g., join.
Journal ArticleDOI
QoS-Aware Web Service Recommendation by Collaborative Filtering
TL;DR: This paper proposes a collaborative filtering approach for predicting QoS values of Web services and making Web service recommendation by taking advantages of past usage experiences of service users, and shows that the algorithm achieves better prediction accuracy than other approaches.
Proceedings ArticleDOI
QoS-based Discovery and Ranking of Web Services
Eyhab Al-Masri,Qusay H. Mahmoud +1 more
TL;DR: The Web service relevancy function (WsRF) used for measuring the relevancies ranking of a particular Web service based on client's preferences, and QoS metrics is introduced and presented.
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