Design and application of augmented reality query-answering system in mobile phone information navigation

Hui Fei Lin*, Chi Hua Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)


This study proposed an augmented reality query-answering system (AR-QAS) based on mobile cloud computing to provide natural language informational navigation services. Empirical research was performed to examine the effectiveness of the system in actual use. This study confirms that the new model developed by combining technology acceptance model (TAM), media richness theory, and the factors of self-efficacy can be applied to relevant AR research. The experiment results revealed that the average question classification accuracy of QAS when combined with artificial neural network and ontology was 98.76%. Moreover, the perceived media richness was found to be positively related to self-efficacy, perceived usefulness, perceived ease of use, user attitude, and use intention. Furthermore, this study reveals that combining the TAM and media richness theory provides a stronger explanation than does the TAM alone. Before new systems are created, designers are suggested to consider the four factors of media richness theory (i.e., multiple cues, language variety, timely feedback, and personal focus), to greatly improve user attitudes toward and behavioral intentions to use new technologies.

Original languageEnglish
Pages (from-to)810-820
Number of pages11
JournalExpert Systems with Applications
Issue number2
Publication statusPublished - 2015 Feb 1
Externally publishedYes


  • Augmented reality
  • Data mining
  • Mobile phone information navigation
  • Query-answering system
  • Technology acceptance model

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence


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