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.
Dominik Ertl and Ralph Hoch did this work while being at the Vienna University of Technology.
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Notes
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In the context of object-oriented software engineering and programming, individuals are typically called instances. Since we follow the model-transformation approach from there in addition to building on ontologies, we use these notions interchangeably in the remainder of this chapter.
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Acknowledgements
This research has been carried out in the SOFAR project (No. 825061), partially funded by the Austrian FIT-IT Program of the FFG.
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Kaindl, H. et al. (2013). Generating Models of Recommendation Processes out of Annotated Ontologies. In: Hussein, T., Paulheim, H., Lukosch, S., Ziegler, J., Calvary, G. (eds) Semantic Models for Adaptive Interactive Systems. Human–Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-4471-5301-6_2
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