Active Learning Genetic programming for record deduplication
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{deFreitas:2010:cec,
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author = "Junio {de Freitas} and Gisele L. Pappa and
Altigran S. {da Silva} and Marcos A. Goncalves and Edleno Moura and
Adriano Veloso and Alberto H. F. Laender and
Moises G. {de Carvalho}",
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title = "Active Learning Genetic programming for record
deduplication",
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booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4244-6910-9",
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URL = "http://www.dcc.ufmg.br/~adrianov/papers/CEC10/cec10.pdf",
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abstract = "The great majority of genetic programming (GP)
algorithms that deal with the classification problem
follow a supervised approach, i.e., they consider that
all fitness cases available to evaluate their models
are labelled. However, in certain application domains,
a lot of human effort is required to label training
data, and methods following a semi-supervised approach
might be more appropriate. This is because they
significantly reduce the time required for data
labelling while maintaining acceptable accuracy rates.
This paper presents the Active Learning GP (AGP), a
semi-supervised GP, and instantiates it for the data
deduplication problem. AGP uses an active learning
approach in which a committee of multi-attribute
functions votes for classifying record pairs as
duplicates or not. When the committee majority voting
is not enough to predict the class of the data pairs, a
user is called to solve the conflict. The method was
applied to three datasets and compared to two other
deduplication methods. Results show that AGP guarantees
the quality of the deduplication while reducing the
number of labeled examples needed.",
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DOI = "doi:10.1109/CEC.2010.5586104",
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notes = "WCCI 2010. Also known as \cite{5586104}",
- }
Genetic Programming entries for
Junio de Freitas
Gisele L Pappa
Altigran S da Silva
Marcos Andre Goncalves
Edleno Silva de Moura
Adriano Veloso
Alberto H F Laender
Moises G de Carvalho
Citations