Web 3.0 in Action: Vector Space Model for Semantic (Movie) Recommendations

27th Symposium On Applied Computing (SAC 2012) - A Technical Track on The Semantic Web and Applications (SWA) - -2012

Authors

Mirizzi Roberto, Di Noia Tommaso, Di Sciascio Eugenio, Ragone Azzurra

Abstract

In this paper we present MORE (acronym of MORE than MOvie REcommendation), a Facebook application that semantically recommends movies to the user leveraging the knowledge within Linked Data and the information elicited from her profile. MORE exploits the power of social knowledge bases (e.g. DBpedia) to detect semantic similarities among movies. These similarities are computed by a Semantic version of the classical Vector Space Model (sVSM), applied to semantic datasets. MORE is freely available as a Facebook application.

DOI

https://doi.org/10.1145/2245276.2245354

BibTex references

@InProceedings{MDDR12,
  author       = "Mirizzi, Roberto and Di Noia, Tommaso and Di Sciascio, Eugenio and Ragone, Azzurra",
  title        = "Web 3.0 in Action: Vector Space Model for Semantic (Movie) Recommendations",
  booktitle    = "27th Symposium On Applied Computing (SAC 2012) - A Technical Track on The Semantic Web and Applications (SWA)",
  year         = "2012",
  publisher    = "ACM",
  url          = "http://sisinflab.poliba.it/Publications/2012/MDDR12"

}