Folksonomies, the Semantic Web, and Movie Recommendation
M. Szomszor, C. Cattuto, H. Alani, K. O'Hara, A. Baldassarri, V. Loreto, and V. Servedio.
4th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0 , (2007)

While the Semantic Web has evolved to support the meaningful exchange of heterogeneous data through shared and controlled conceptualisations, Web 2.0 has demonstrated that large-scale community tagging sites can enrich the semantic web with readily accessible and valuable knowledge. In this paper, we investigate the integration of a movies folksonomy with a semantic knowledge base about user-movie rentals. The folksonomy is used to enrich the knowledge base with descriptions and categorisations of movie titles, and user interests and opinions. Using tags harvested from the Internet Movie Database, and movie rating data gathered by Netflix, we perform experiments to investigate the question that folksonomy-generated movie tag-clouds can be used to construct better user profiles that reflect a user's level of interest in different kinds of movies, and therefore, provide a basis for prediction of their rating for a previously unseen movie.

Document: http://eprints.soton.ac.uk/264007/1/ESWC2007.pdf
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@inproceedings{ecs14007,
  abstract = {While the Semantic Web has evolved to support the meaningful exchange of
heterogeneous data through shared and controlled conceptualisations, Web 2.0
has demonstrated that large-scale community tagging sites can enrich the
semantic web with readily accessible and valuable knowledge. In this paper,
we investigate the integration of a movies folksonomy with a semantic
knowledge base about user-movie rentals. The folksonomy is used to enrich the
knowledge base with descriptions and categorisations of movie titles, and
user interests and opinions. Using tags harvested from the Internet Movie
Database, and movie rating data gathered by Netflix, we perform experiments
to investigate the question that folksonomy-generated movie tag-clouds can be used to
construct better user profiles that reflect a user's level of interest in
different kinds of movies, and therefore, provide a basis for prediction of
their rating for a previously unseen movie.},
  added-at = {2016-07-30T22:45:02.000+0200},
  author = {Szomszor, Martin and Cattuto, Ciro and Alani, Harith and O'Hara, Kieron and Baldassarri, Andrea and Loreto, Vittorio and Servedio, Vito D.P.},
  biburl = {https://www.bibsonomy.org/bibtex/249680fc824068caf13167748f55e9141/nosebrain},
  booktitle = {4th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0},
  interhash = {1f9f83649c25b88e43bbb54494496be8},
  intrahash = {49680fc824068caf13167748f55e9141},
  keywords = {},
  timestamp = {2016-07-30T22:45:02.000+0200},
  title = {Folksonomies, the Semantic Web, and Movie Recommendation},
  url = {http://eprints.soton.ac.uk/264007/1/ESWC2007.pdf},
  year = 2007
}

%0 Conference Paper
%1 ecs14007
%A Szomszor, Martin
%A Cattuto, Ciro
%A Alani, Harith
%A O'Hara, Kieron
%A Baldassarri, Andrea
%A Loreto, Vittorio
%A Servedio, Vito D.P.
%B 4th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0
%D 2007
%K 
%T Folksonomies, the Semantic Web, and Movie Recommendation
%U http://eprints.soton.ac.uk/264007/1/ESWC2007.pdf
%X While the Semantic Web has evolved to support the meaningful exchange of
heterogeneous data through shared and controlled conceptualisations, Web 2.0
has demonstrated that large-scale community tagging sites can enrich the
semantic web with readily accessible and valuable knowledge. In this paper,
we investigate the integration of a movies folksonomy with a semantic
knowledge base about user-movie rentals. The folksonomy is used to enrich the
knowledge base with descriptions and categorisations of movie titles, and
user interests and opinions. Using tags harvested from the Internet Movie
Database, and movie rating data gathered by Netflix, we perform experiments
to investigate the question that folksonomy-generated movie tag-clouds can be used to
construct better user profiles that reflect a user's level of interest in
different kinds of movies, and therefore, provide a basis for prediction of
their rating for a previously unseen movie.

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Folksonomies, the Semantic Web, and Movie Recommendation
M. Szomszor, C. Cattuto, H. Alani, K. O'Hara, A. Baldassarri, V. Loreto, and V. Servedio.
4th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0 , (2007)

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Folksonomies, the Semantic Web, and Movie RecommendationM. Szomszor, C. Cattuto, H. Alani, K. O'Hara, A. Baldassarri, V. Loreto, and V. Servedio. 4th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0 , (2007)

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Cite this publication

Folksonomies, the Semantic Web, and Movie Recommendation
M. Szomszor, C. Cattuto, H. Alani, K. O'Hara, A. Baldassarri, V. Loreto, and V. Servedio.
4th European Semantic Web Conference, Bridging the Gap between Semantic Web and Web 2.0 , (2007)