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Since many mobile services have been or being developed as the interfaces to access resources on mobile environment, the number of services increases dramatically.
Users often have to select a mobile service from a series of service candidates with similar function.
It can be seen that the prediction accuracy of CF algorithm largely depends on the identification of similar neighbors.
So it is difficult to conduct similar neighbor identification with high accuracy in sparse Qo S records.
So we decide to propose new models that can handle the above issues, and our models are based on Slope One model.
For Qo S prediction, the Slope One model does not need to identify similar neighbors but directly uses the known Qo S records to predict missing values .
So the Slope One model avoids the issue of similar neighbor identification that happens in CF algorithm.