Contact Project Developer Ashish D. Tiwari [astiwz@gmail.com]
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A Highly Accurate Prediction Algorithm for Unknown Web Service QoS Values

Algorithm for Unknown Web Service QoS Values
Abstract-Synopsis-Documentation

<h1>A Highly Accurate Prediction Algorithm for Unknown Web Service QoS Values </h1>


ABSTRACT

Quality of Service (QoS) guarantee is an important component of service recommendation. Generally, some QoS values of a service are unknown to its users who has never invoked it before, and therefore the accurate prediction of unknown QoS values is significant for the successful deployment of Web service-based applications. Collaborative filtering is an important method for predicting missing values, and has thus been widely adopted in the prediction of unknown QoS values. However, collaborative filtering originated from the processing of subjective data, such as movie scores. The QoS data of Web services are usually objective, meaning that existing collaborative filtering-based approaches are not always applicable for unknown QoS values. Based on real world Web service QoS data and a number of experiments, in this paper, we determine some important characteristics of objective QoS datasets that have never been found before. We propose a prediction algorithm to realize these characteristics, allowing the unknown QoS values to be predicted accurately. Experimental results show that the proposed algorithm predicts unknown Web service QoS values more accurately than other existing approaches.


PROPOSED SYSTEM

Based on these characteristics, we proposed our HAPA ( Hapa is a term used to describe a person of mixed HYPERLINK "https://en.wikipedia.org/wiki/Ethnic_group" \o "Ethnic group"ethnic heritage) .The prediction accuracy of HAPA was shown to outperform that of many of existing QoS prediction methods. As the definition of Objective Data, Web service QoS is determined as a result of some objective factors, such as network traffic, bandwidth, when and where a user accessed a Web service. Our proposed HAPA does not predict unknown QoS values by these objective factors, but directly by the known QoS values. We can make predictions even more accurately if we know the relationship between these objective factors and the final QoS. To work out this relationship, we still have some important problems to solve, such as finding the core objective factors, how observe these objective factors, how probe user context and how learn this relationship. we propose a Web service QoS value prediction algorithm HAPA to realize these characteristics, allowing the unknown QoS values to be predicted accurately. Finally, we conduct several real world experiments to verify our prediction accuracy.  

Specifically, our key contributions are as follows. 

We are trying to solve these problems and will propose our approaches in the future work. 

We propose a prediction algorithm to realize these characteristics, allowing the unknown QoS values to be predicted accurately. 

Doctor and patient relationship measured by hospital management in case Qos values denoted which one is the better approach.  

Experimental results show that the proposed algorithm predicts unknown Web service QoS values more accurately than other existing approaches.


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