A Semantic Hybrid Approach for Sound Recommendation

A Semantic Hybrid Approach for Sound Recommendation

24th World Wide Web Conference - -2015

Authors

Ostuni Vito Claudio, Oramas Sergio, Di Noia Tommaso, Serra Xavier, Di Sciascio Eugenio

Abstract

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.

Download: A Semantic Hybrid Approach for Sound Recommendation - WWW 2015.pdf

DOI

https://doi.org/10.1145/2740908.2742775

BibTex 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"

}