Advanced clustering methods for mining chemical databases in forensic science
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{Ratle2008123,
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author = "Frederic Ratle and Christian Gagne and
Anne-Laure Terrettaz-Zufferey and Mikhail Kanevski and
Pierre Esseiva and Olivier Ribaux",
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title = "Advanced clustering methods for mining chemical
databases in forensic science",
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journal = "Chemometrics and Intelligent Laboratory Systems",
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volume = "90",
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number = "2",
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pages = "123--131",
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year = "2008",
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ISSN = "0169-7439",
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URL = "http://sites.google.com/site/fredericratle/ratle_gagne_chemo.pdf",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.134.7959",
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DOI = "doi:10.1016/j.chemolab.2007.09.001",
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URL = "http://www.sciencedirect.com/science/article/B6TFP-4PMT2KM-1/2/e248214c0a37620fa970bc9a2020a7c2",
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keywords = "genetic algorithms, genetic programming, Forensic
science, Machine learning, Pattern analysis, Spectral
clustering, Kernel methods, Gas chromatography",
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language = "en",
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oai = "oai:CiteSeerXPSU:10.1.1.134.7959",
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abstract = "Heroin and cocaine gas chromatography data are
analyzed using several clustering techniques. A
database with clusters confirmed by police
investigation is used to assess the potential of the
analysis of the chemical signature of these drugs in
the investigation process. Results are compared to
standard methods in the field of chemical drug
profiling and show that conventional approaches miss
the inherent structure in the data, which is
highlighted by methods such as spectral clustering and
its variants. Also, an approach based on genetic
programming is presented in order to tune the affinity
matrix of the spectral clustering algorithm. Results
indicate that all algorithms show a quite different
behavior on the two datasets, but in both cases, the
data exhibits a level of clustering, since there is at
least one type of clustering algorithm that performs
significantly better than chance. This confirms the
relevancy of using chemical drugs databases in the
process of understanding the illicit drugs market, as
information regarding drug trafficking networks can
likely be extracted from the chemical composition of
drugs.",
- }
Genetic Programming entries for
Frederic Ratle
Christian Gagne
Anne-Laure Terrettaz-Zufferey
Mikhail F Kanevski
Pierre Esseiva
Olivier Ribaux
Citations