Solving data preprocessing problems in existing location-aware systems

Tin-Chih Chen, Katsuhiro Honda*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)253-259
Number of pages7
JournalJournal of Ambient Intelligence and Humanized Computing
Volume9
Issue number2
DOIs
StatePublished - 1 Apr 2018

Keywords

  • Big data
  • Linearization
  • Location-based service
  • Nonlinearization
  • Normalization
  • Utility

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