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M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 5 Issue 12, December 2016

An Overview of Accurate Prediction Model for Web Services

Moodu Jyothi | Tejaswini ^[23]

Abstract: Collaborative filtering is a vital way of predicting missing values, and it has thus been broadly adopted within the conjecture of unknown QoS values. However, collaborative filtering came from in the processing of subjective data, for example movie scores. Traditional CF is dependent on the idea that similar customers have similar subjective experience on single products, however these premise no more is applicable for that objective data. According to real life Web service QoS data and numerous experiments, within this paper, we determine some important qualities of objective QoS datasets which have never been found before. We advise a conjecture formula to understand these qualities, permitting the unknown QoS values to become predicted precisely. We present a very accurate conjecture formula (HAPA) for unknown Web service QoS values.

Keywords: Collaborative filtering, Web service, QoS datasets, Highly accurate prediction algorithm

Edition: Volume 5 Issue 12, December 2016,

Pages: 1114 - 1117

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