Recommendation Techniques on a Knowledge Graph for Email Remarketing
نویسندگان
چکیده
The knowledge graph, which is an ontology based representation technique, is described to model the information necessary to conduct collaborative filtering, content-based filtering and knowledge based recommendation methods. Spreading activation and network science based recommendation methods are presented and evaluated. The evaluation measures are calculated on top list recommendations, where rating estimation is not necessary. In the experiment, click-through rates are measured and presented based on the email based remarketing activity of an electronic commerce system. Our primary result shows the improved recommendation quality of spreading activation based methods compared to the human expert. Keywords–knowledge graph; recommender system; spreading activation; network science; email remarketing
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