Modelling User Preferences with Multi-Instance Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Zafra:2008:IPMU,
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author = "Amelia Zafra and Sebastian Ventura",
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title = "Modelling User Preferences with Multi-Instance Genetic
Programming",
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booktitle = "Information processing and Management of Uncertainty
in Knowledge based systems, IPMU 20018",
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year = "2008",
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editor = "Luis Magdalena and Jose Luis Verdegay",
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address = "Malaga, Spain",
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month = jun # " 22-27",
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keywords = "genetic algorithms, genetic programming, user
modelling, recommender systems, multi-instance
learning, multi- objective algorithms",
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annote = "The Pennsylvania State University CiteSeerX Archives",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.473.4886",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
-
URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.473.4886",
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URL = "http://www.gimac.uma.es/ipmu08/proceedings/papers/148-zafraventura.pdf",
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URL = "http://www.gimac.uma.es/ipmu08/proceedings/html/148.html",
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abstract = "In this paper we introduce a novel model for providing
users with recommendations about web index pages of
their interests. The approach proposed developes user
profiles based on evolutionary multi instance learning
which determines what users find interesting and
uninteresting by means of rules which add
comprehensibility and clarity to user models and
increase the quality of the recommendations.
Experimental results show that our methodology achieves
competitive results, providing high-quality user models
which improve the accuracy of recommendations.",
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notes = "http://www.gimac.uma.es/ipmu08/",
- }
Genetic Programming entries for
Amelia Zafra Gomez
Sebastian Ventura
Citations