Vito Claudio Ostuni
Tommaso Di Noia
Sergio Oramas
ABSTRACT
In 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.
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Digital Library
- Frederic Font and Sergio Oramas. Extending Tagging Ontologies with Domain Specific Knowledge. Interantional Semantic Web Conference (ISWC 2014), pages 1--4, 2014.Google Scholar
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Index Terms
- A Semantic Hybrid Approach for Sound Recommendation
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