Demo – Paper 569

CityMUS: Music Recommendation When Exploring a City

Pasquale Lisena, Lorenzo Canale, Fabio Ellena and Raphaël Troncy

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Abstract

Linked Data makes possible the discovery of interesting connections between semantic entities that belong to different domains. This paper presents CityMUS, a web application that gives to the user the experience of a walk in the city with the most suitable soundtrack, on the base of the urban context. The application relies on a recommender system that searches for paths in a knowledge graph between nearby places and music composers, making use of a combination of DBpedia and domain-specific datasets.

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