A Semantic Hybrid Approach for Sound Recommendation
24th World Wide Web Conference - -2015
Ostuni Vito Claudio, Oramas Sergio, Di Noia Tommaso
, Serra Xavier, Di Sciascio Eugenio
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
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"