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Automatic learning of user interests for personalized communication services

Matthias Strobbe (UGent) and Olivier Van Laere
(2008) UGent-FirW Doctoraatssymposium, 9e. p.168-169
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Abstract
In view of the overwhelming popularity of user generated content new intelligent services are needed to filter this content based on personal interests. In this paper we present a set of algorithms for retrieving content, based on dynamic user profiles and learning capabilities. To illustrate the approach taken, a rich communication service is presented.

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Citation

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MLA
Strobbe, Matthias, and Olivier Van Laere. “Automatic Learning of User Interests for Personalized Communication Services.” UGent-FirW Doctoraatssymposium, 9e, Universiteit Gent. Faculteit Ingenieurswetenschappen, 2008, pp. 168–69.
APA
Strobbe, M., & Van Laere, O. (2008). Automatic learning of user interests for personalized communication services. UGent-FirW Doctoraatssymposium, 9e, 168–169. Gent: Universiteit Gent. Faculteit Ingenieurswetenschappen.
Chicago author-date
Strobbe, Matthias, and Olivier Van Laere. 2008. “Automatic Learning of User Interests for Personalized Communication Services.” In UGent-FirW Doctoraatssymposium, 9e, 168–69. Gent: Universiteit Gent. Faculteit Ingenieurswetenschappen.
Chicago author-date (all authors)
Strobbe, Matthias, and Olivier Van Laere. 2008. “Automatic Learning of User Interests for Personalized Communication Services.” In UGent-FirW Doctoraatssymposium, 9e, 168–169. Gent: Universiteit Gent. Faculteit Ingenieurswetenschappen.
Vancouver
1.
Strobbe M, Van Laere O. Automatic learning of user interests for personalized communication services. In: UGent-FirW Doctoraatssymposium, 9e. Gent: Universiteit Gent. Faculteit Ingenieurswetenschappen; 2008. p. 168–9.
IEEE
[1]
M. Strobbe and O. Van Laere, “Automatic learning of user interests for personalized communication services,” in UGent-FirW Doctoraatssymposium, 9e, Gent, 2008, pp. 168–169.
@inproceedings{674424,
  abstract     = {{In view of the overwhelming popularity of user generated content new intelligent services are needed to filter this content based on personal interests. In this paper we present a set of algorithms for retrieving content, based on dynamic user profiles and learning capabilities. To illustrate the approach taken, a rich communication service is presented.}},
  author       = {{Strobbe, Matthias and Van Laere, Olivier}},
  booktitle    = {{UGent-FirW Doctoraatssymposium, 9e}},
  language     = {{eng}},
  location     = {{Gent}},
  pages        = {{168--169}},
  publisher    = {{Universiteit Gent. Faculteit Ingenieurswetenschappen}},
  title        = {{Automatic learning of user interests for personalized communication services}},
  url          = {{http://users.elis.ugent.be/~pbertels/zijspoor/phd/2008_a050.pdf}},
  year         = {{2008}},
}