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

Raso, Rocco
Werth, Dirk
Loos, Peter
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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.
Augmented Reality, Content Creation, Content Management, Hybrid Media, Print Media
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