Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/11428
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dc.contributor.authorPerakakis, E-
dc.contributor.authorGhinea, G-
dc.date.accessioned2015-09-30T10:48:17Z-
dc.date.available2015-08-01-
dc.date.available2015-09-30T10:48:17Z-
dc.date.issued2015-
dc.identifier.citationIEEE Transactions on Human-Machine Systems, 45(4): pp. 534 - 539, (2015)en_US
dc.identifier.issn2168-2291-
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7059247-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/11428-
dc.description.abstractDeveloping an interactive TV Commercial (iTVC) for Internet connected TVs is complicated by the number of different platforms, each with its own operating system and application programming interface (API). To achieve cross-platform compatibility, we propose to use standard web technologies, instead of proprietary APIs for each device. With our approach, only one iTVC was developed, which contained commonly used features of these kinds of advertisements, and used only web technologies (HTML5, CSS, and JavaScript). The iTVC was first developed on a desktop personal computer and was tested on three different smart TV platforms for feature compatibility. After achieving compatibility, a user study with 36 participants evaluated how platform-related differences affect aspects of user experience (UX) and effectiveness of the interactive ad. The measured UX/effectiveness aspects and usability were consistent regardless of the iTVC performance on each device. These results show the potential of web technologies to deliver a uniform (and effective) interactive Ad across a range of heterogeneous devices.en_US
dc.format.extent534 - 539-
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectInteractive TV Advertisingen_US
dc.subjectSmart TV Advertisingen_US
dc.subjectt-commerceen_US
dc.subjectUser experienceen_US
dc.titleHTML5 technologies for effective cross-platform interactive/smart TV advertisingen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1109/THMS.2015.2401975-
dc.relation.isPartOfIEEE Transactions on Human-Machine Systems-
pubs.issue4-
pubs.volume45-
Appears in Collections:Dept of Computer Science Research Papers

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