Using Semantic Relations for Content-based Recommender Systems in Cultural heritage

Metadata vocabularies provide various semantic relationsbetween concepts. For content-based recommender systems, these rela-tions enable a wide range of concepts to be recommended. However, notall semantically related concepts are interesting for end users. In this pa-per, we identified a number of semantic relations, which are within onevocabulary (e.g. a concept has a broader/narrower concept) and acrossmultiple vocabularies (e.g. an artist is associated to an art style). Ourgoal is to investigate which semantic relations are useful for recommenda-tions of art concepts and to look at the combined use of artwork featuresand semantic relations in sequence. These sequences of ratings allow usto derive some navigation patterns from users, which might enhance theaccuracy of recommendations and be reused for other recommender sys-tems in similar domains. We tested the CHIP demonstrator, called theArt Recommender with end users by recommending both semantically-related concepts and artworks features (e.g.creator, material, subject)