Embedding Knowledge Graphs for Semantics-aware Recommendations based on DBpedia

ADJUNCT PUBLICATION OF THE 27TH CONFERENCE ON USER MODELING, ADAPTATION AND PERSONALIZATION (ACM UMAP '19 ADJUNCT), pp. 27-31, 2019.

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Abstract:

In this paper we present a semantics-aware recommendation strategy that uses graph embedding techniques to learn a vector space representation of the items to be recommended. Such a representation relies on the tripartite graph which connects users, items and entities gathered from DBpedia, thus it encodes both collaborative and content-b...More

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