Capturing knowledge of user preferences: ontologies in recommender systems
S. Middleton, D. Roure, and N. Shadbolt.
K-CAP '01: Proceedings of the 1st international conference on Knowledge capture, page 100--107. New York, NY, USA, ACM, (2001)

Tools for filtering the World Wide Web exist, but they are hampered by the difficulty of capturing user preferences in such a dynamic environment. We explore the acquisition of user profiles by unobtrusive monitoring of browsing behaviour and application of supervised machine-learning techniques coupled with an ontological representation to extract user preferences. A multi-class approach to paper classification is used, allowing the paper topic taxonomy to be utilised during profile construction. The Quickstep recommender system is presented and two empirical studies evaluate it in a real work setting, measuring the effectiveness of using a hierarchical topic ontology compared with an extendable flat list.

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@inproceedings{middleton01,
  abstract = {Tools for filtering the World Wide Web exist, but they are hampered by the difficulty of capturing user preferences in such a dynamic environment. We explore the acquisition of user profiles by unobtrusive monitoring of browsing behaviour and application of supervised machine-learning techniques coupled with an ontological representation to extract user preferences. A multi-class approach to paper classification is used, allowing the paper topic taxonomy to be utilised during profile construction. The Quickstep recommender system is presented and two empirical studies evaluate it in a real work setting, measuring the effectiveness of using a hierarchical topic ontology compared with an extendable flat list.},
  added-at = {2008-12-19T15:24:17.000+0100},
  address = {New York, NY, USA},
  author = {Middleton, Stuart E. and Roure, David C. De and Shadbolt, Nigel R.},
  biburl = {https://puma.uni-kassel.de/bibtex/26d0a7792db2c0f96bd0a495a56e57464/jaeschke},
  booktitle = {K-CAP '01: Proceedings of the 1st international conference on Knowledge capture},
  description = {Capturing knowledge of user preferences},
  doi = {http://doi.acm.org/10.1145/500737.500755},
  interhash = {332dfc15a8f0fc442b47a9a4b740b1bf},
  intrahash = {6d0a7792db2c0f96bd0a495a56e57464},
  isbn = {1-58113-380-4},
  keywords = {knowledge ontology recommender webzu},
  location = {Victoria, British Columbia, Canada},
  pages = {100--107},
  publisher = {ACM},
  timestamp = {2008-12-19T15:24:17.000+0100},
  title = {Capturing knowledge of user preferences: ontologies in recommender systems},
  url = {http://portal.acm.org/citation.cfm?id=500737.500755},
  year = 2001
}

%0 Conference Paper
%1 middleton01
%A Middleton, Stuart E.
%A Roure, David C. De
%A Shadbolt, Nigel R.
%B K-CAP '01: Proceedings of the 1st international conference on Knowledge capture
%C New York, NY, USA
%D 2001
%I ACM
%K knowledge ontology recommender webzu
%P 100--107
%R http://doi.acm.org/10.1145/500737.500755
%T Capturing knowledge of user preferences: ontologies in recommender systems
%U http://portal.acm.org/citation.cfm?id=500737.500755
%X Tools for filtering the World Wide Web exist, but they are hampered by the difficulty of capturing user preferences in such a dynamic environment. We explore the acquisition of user profiles by unobtrusive monitoring of browsing behaviour and application of supervised machine-learning techniques coupled with an ontological representation to extract user preferences. A multi-class approach to paper classification is used, allowing the paper topic taxonomy to be utilised during profile construction. The Quickstep recommender system is presented and two empirical studies evaluate it in a real work setting, measuring the effectiveness of using a hierarchical topic ontology compared with an extendable flat list.
%@ 1-58113-380-4

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Capturing knowledge of user preferences: ontologies in recommender systems
S. Middleton, D. Roure, and N. Shadbolt.
K-CAP '01: Proceedings of the 1st international conference on Knowledge capture, page 100--107. New York, NY, USA, ACM, (2001)

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PUMA

Capturing knowledge of user preferences: ontologies in recommender systemsS. Middleton, D. Roure, and N. Shadbolt. K-CAP '01: Proceedings of the 1st international conference on Knowledge capture, page 100--107. New York, NY, USA, ACM, (2001)

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Capturing knowledge of user preferences: ontologies in recommender systems
S. Middleton, D. Roure, and N. Shadbolt.
K-CAP '01: Proceedings of the 1st international conference on Knowledge capture, page 100--107. New York, NY, USA, ACM, (2001)