A Semantic Hybrid Approach for Sound Recommendation
Authors
Ostuni Vito Claudio, Oramas Sergio, Di Noia Tommaso, Serra Xavier, Di Sciascio EugenioAbstract
n 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
https://doi.org/10.1145/2740908.2742775BibTex references
@InProceedings{OODSD15, author = "Ostuni, Vito Claudio and Oramas, Sergio and Di Noia, Tommaso and Serra, Xavier and Di Sciascio, Eugenio", title = "A Semantic Hybrid Approach for Sound Recommendation", booktitle = "24th World Wide Web Conference", year = "2015", publisher = "ACM", url = "http://sisinflab.poliba.it/Publications/2015/OODSD15" }