A Semantic Hybrid Approach for Sound Recommendation

TitleA Semantic Hybrid Approach for Sound Recommendation
Publication TypeConference Paper
Year of Publication2015
Conference Name24th International World Wide Web Conference (WWW 2015)
AuthorsOstuni, V. C., Oramas S., Di Noia T., Serra X., & Di Sciascio E.
Conference Start Date18/05/2015
PublisherSheridan Communications
Conference LocationFlorence, Italy
AbstractIn this work we describe a hybrid recommendation approach for recommending sounds to users by exploiting and semantically enriching textual information such as tags and sounds descriptions. As a case study we used Freesound, a popular site for sharing sound samples which counts more than 4 million registered users. Tags and textual sound descriptions are exploited to extract and link entities to external ontologies such as WordNet and DBpedia. The enriched data are eventually merged with a domain specific tagging ontology to form a knowledge graph. Based on this latter, recommendations are then computed using a semantic version of the feature combination hybrid approach. An evaluation on historical data shows improvements with respect to state of the art collaborative algorithms.
DOI of final publicationhttp://dx.doi.org/10.1145/2740908.2742775