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An Enhanced QoS Prediction Approach for Service Selection

Authors: Liang Chen 0001; Yipeng Feng; Jian Wu 0001; Zibin Zheng;

An Enhanced QoS Prediction Approach for Service Selection

Abstract

In this paper, we propose an enhanced QoS prediction approach to predict the missing QoS values for QoS-based selection. Compared with existing QoS prediction methods, our proposed A Smooth approach has two differences: 1) using A-cosine equation for similarity calculation to remove the impact of different QoS scale, 2) adding a data Smoothing process to improve the prediction accuracy. An extensive performance study based on a real public dataset is reported to verify the prediction accuracy of our proposed approach.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
30
Top 10%
Top 10%
Top 10%
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