Solving data preprocessing problems in existing location-aware systems

Location-aware services, or location-based services, are widely available and guide users to suitable service locations by considering distance and other contextual information. Despite the success stories reported by previous research, the formulae developed for evaluating the utility of a service location in existing location-aware service systems have discrepancies. Examining several representative cases revealed that most of these discrepancies were caused by improper data preprocessing, including huge data, incomplete data normalization, subjective data linearization or nonlinearization, biased weight adjustment, and information-loss discretization. This study reviews these discrepancies and provides corrections for overcoming them.

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