Enriching Augmented Reality with Text Data Mining: An Automated Content Management System to Develop Hybrid Media Applications

dc.contributor.author Raso, Rocco
dc.contributor.author Werth, Dirk
dc.contributor.author Loos, Peter
dc.date.accessioned 2016-12-29T02:16:42Z
dc.date.available 2016-12-29T02:16:42Z
dc.date.issued 2017-01-04
dc.description.abstract Augmented Reality (AR) tools offer novel typologies of contents to generate Augmented Print (AP) systems. Compared with traditional print media, the development of AP applications requires additional efforts to identify thematic contents, which are suitable to be enhanced by AR systems. The generation of virtual contents represents a potential obstacle for developing AP applications. Motivated by the necessity to provide hybrid media applications with more efficient tools, in this paper we present a novel paradigm, which employs an automated framework to face the issue of content creation and content management. We propose a model for the automatic detection of specific textual contents in traditional print media. Using techniques from text data mining, we identify virtual contents which match the editorial contents. This aids in the process of content creation and management and, as a result, simplifies AR content delivery and shapes new perspectives for hybrid media applications.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2017.746
dc.identifier.isbn 978-0-9981331-0-2
dc.identifier.uri http://hdl.handle.net/10125/41910
dc.language.iso eng
dc.relation.ispartof Proceedings of the 50th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Augmented Reality
dc.subject Content Creation
dc.subject Content Management
dc.subject Hybrid Media
dc.subject Print Media
dc.title Enriching Augmented Reality with Text Data Mining: An Automated Content Management System to Develop Hybrid Media Applications
dc.type Conference Paper
dc.type.dcmi Text
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
paper0761.pdf
Size:
1.14 MB
Format:
Adobe Portable Document Format
Description: