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Semantics and Ontologies for Feedback-driven Adapting Recommender Systems


Consumers increasingly buy products through the Internet, but they lack assistance for searching the “right” product. Recommender systems address this problem by asking targeted questions. The success (or failure) of such a recommendation process is defined in terms of conversion rate or click-out rate. It is very difficult to predict improvements for given changes of the recommendation process, however, and manual changes are usually very expensive.   Therefore, SOFAR ("Semantics and Ontologies for Feedback-driven Adapting Recommender Systems") proposes automated adaptations of recommendation processes making use of semantic technology. The approach makes Internet content accessible for searching products.

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