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QoS Recommendation in Cloud Services | IEEE Journals & Magazine | IEEE Xplore

QoS Recommendation in Cloud Services


As illustrated here, a collaborative filtering approach using the Pearson coefficient makes a mistake in its ranking, whereas a collaborative filtering approach using the...

Abstract:

As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of service (QoS), which describe...Show More
Topic: Curbing Crowdturfing in Online Social Networks

Abstract:

As cloud computing becomes increasingly popular, cloud providers compete to offer the same or similar services over the Internet. Quality of service (QoS), which describes how well a service is performed, is an important differentiator among functionally equivalent services. It can help a firm to satisfy and win its customers. As a result, how to assist cloud providers to promote their services and cloud consumers to identify services that meet their QoS requirements becomes an important problem. In this paper, we argue for QoS-based cloud service recommendation, and propose a collaborative filtering approach using the Spearman coefficient to recommend cloud services. The approach is used to predict both QoS ratings and rankings for cloud services. To evaluate the effectiveness of the approach, we conduct extensive simulations. Results show that the approach can achieve more reliable rankings, yet less accurate ratings, than a collaborative filtering approach using the Pearson coefficient.
Topic: Curbing Crowdturfing in Online Social Networks
As illustrated here, a collaborative filtering approach using the Pearson coefficient makes a mistake in its ranking, whereas a collaborative filtering approach using the...
Published in: IEEE Access ( Volume: 5)
Page(s): 5171 - 5177
Date of Publication: 19 April 2017
Electronic ISSN: 2169-3536

References

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