Using mobile device detection approaches to augment the accuracy of web delivery content


Autoria(s): Queirós, Ricardo; Pinto, Mário
Data(s)

24/10/2014

24/10/2014

2011

Resumo

Recent studies of mobile Web trends show a continuous explosion of mobile-friendly content. However, the increasing number and heterogeneity of mobile devices poses several challenges for Web programmers who want to automatically get the delivery context and adapt the content to mobile devices. In this process, the devices detection phase assumes an important role where an inaccurate detection could result in a poor mobile experience for the enduser. In this paper we compare the most promising approaches for mobile device detection. Based on this study, we present an architecture for a system to detect and deliver uniform m-Learning content to students in a Higher School. We focus mainly on the devices capabilities repository manageable and accessible through an API. We detail the structure of the capabilities XML Schema that formalizes the data within the devices capabilities XML repository and the REST Web Service API for selecting the correspondent devices capabilities data according to a specific request. Finally, we validate our approach by presenting the access and usage statistics of the mobile web interface of the proposed system such as hits and new visitors, mobile platforms, average time on site and rejection rate.

Identificador

9789899686311

http://hdl.handle.net/10400.22/5096

Idioma(s)

eng

Publicador

ESEIG

Direitos

openAccess

Palavras-Chave #Device detection #XML repositories #M-learning
Tipo

conferenceObject