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Semantic Models for Adaptive Interactive SystemsGenerating Models of Recommendation Processes out of Annotated Ontologies

Semantic Models for Adaptive Interactive Systems: Generating Models of Recommendation Processes... [Creating content- and dialogue-based recommendation processes through manual adaptations requires a lot of time and effort. Therefore, automated generation of such processes is desirable. We present an approach for generating models of recommendation processes out of annotated ontologies. Such product ontologies have to be provided manually, but certain adaptations to them can be discovered from unstructured data (customer-generated content such as blog entries or customer feedback on products in the Web). They are given input for our approach, which applies semantic model-driven transformations to these ontologies for generating discourse-based models of recommendation processes on a high conceptual level first. These generated discourses essentially consist of questions and answers about those items annotated as important in the ontologies, and their possible sequences. From such a high-level model, transformation rules create a model of an operationalized recommendation process. This model also represents a so-called concrete user interface and consists of both the structure of the process and the course of events, which defines how customers may navigate through the process. From such models, an already given infrastructure can generate running processes including their final user interfaces, which have already been deployed successfully for real-world use.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Semantic Models for Adaptive Interactive SystemsGenerating Models of Recommendation Processes out of Annotated Ontologies

Part of the Human–Computer Interaction Series Book Series
Editors: Hussein, Tim; Paulheim, Heiko; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle
Kaindl, Hermann; Ertl, Dominik; Popp, Roman; Hoch, Ralph; Falb, Jürgen; Arnautovic, Edin; Okoli, Ada; Schliefnig, Martin
Semantic Models for Adaptive Interactive Systems — May 14, 2013
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18 pages

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Publisher
Springer London
Copyright
© Springer-Verlag London 2013
ISBN
978-1-4471-5300-9
Pages
25 –42
DOI
10.1007/978-1-4471-5301-6_2
Publisher site
See Chapter on Publisher Site

Abstract

[Creating content- and dialogue-based recommendation processes through manual adaptations requires a lot of time and effort. Therefore, automated generation of such processes is desirable. We present an approach for generating models of recommendation processes out of annotated ontologies. Such product ontologies have to be provided manually, but certain adaptations to them can be discovered from unstructured data (customer-generated content such as blog entries or customer feedback on products in the Web). They are given input for our approach, which applies semantic model-driven transformations to these ontologies for generating discourse-based models of recommendation processes on a high conceptual level first. These generated discourses essentially consist of questions and answers about those items annotated as important in the ontologies, and their possible sequences. From such a high-level model, transformation rules create a model of an operationalized recommendation process. This model also represents a so-called concrete user interface and consists of both the structure of the process and the course of events, which defines how customers may navigate through the process. From such models, an already given infrastructure can generate running processes including their final user interfaces, which have already been deployed successfully for real-world use.]

Published: May 14, 2013

Keywords: Recommendation Process; Discourse-based Models; Final User Interface; Business Process Model And Notation (BPMN); Semi-automatic Generation

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