Design and application of augmented reality query-answering system in mobile phone information navigation. Issue 2 (1st February 2015)

• Record Type: Journal Article
• Authors: Lin, Hui-Fei; Chen, Chi-Hua
• Is Part Of: Expert systems with applications. Volume 42:Issue 2(2015)
• Page Start: 810
• Page End: 820
• Publication Date: 2015-02-01
• Subjects: Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.07.050
• Languages: English
• ISSNs: 0957-4174

Abstract

<abstract xml:lang="en" abstract-type="author-highlights" id="ab005"> <title id="st175">Highlights</title> <sec> <p id="sp0005"> <list id="l0005"> <list-item id="o0005"> <label></label> <p id="p0385">An augmented reality query-answering system (AR-QAS) is designed and implemented in this study.</p> </list-item> <list-item id="o0010"> <label></label> <p id="p0390">The average question classification accuracy in an artificial neural network was 98.76%.</p> </list-item> <list-item id="o0015"> <label></label> <p id="p0395">AR-QAS can provide a fast and convenient mobile information navigation service for users.</p> </list-item> <list-item id="o0020"> <label></label> <p id="p0400">Language variety, timely feedback, and personal focus improve behavioral intentions to us AR-QAS.</p> </list-item> <list-item id="o0025"> <label></label> <p id="p0405">This study confirms that the new model combining TAM and MRT can be applied to relevant AR research.</p> </list-item> </list> </p> </sec> </abstract>