Knowledge mining sensory evaluation data: genetic programming, statistical techniques, and swarm optimization
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Veeramachaneni:2012:GPEM,
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author = "Kalyan Veeramachaneni and Ekaterina Vladislavleva and
Una-May O'Reilly",
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title = "Knowledge mining sensory evaluation data: genetic
programming, statistical techniques, and swarm
optimization",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2012",
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volume = "13",
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number = "1",
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pages = "103--133",
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month = mar,
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note = "Special Section on Evolutionary Algorithms for Data
Mining",
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keywords = "genetic algorithms, genetic programming, food, scent,
flavor, Symbolic regression, Sensory science,
Ensembles, Non-linear optimisation, Variable selection,
Pareto, Hedonic evaluation, Complexity control, PSO,
bloat",
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ISSN = "1389-2576",
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DOI = "doi:10.1007/s10710-011-9153-2",
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size = "31 pages",
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abstract = "Knowledge mining sensory evaluation data is a
challenging process due to extreme sparsity of the
data, and a large variation in responses from different
members (called assessors) of the panel. The main goals
of knowledge mining in sensory sciences are
understanding the dependency of the perceived liking
score on the concentration levels of flavours'
ingredients, identifying ingredients that drive liking,
segmenting the panel into groups with similar liking
preferences and optimising flavors to maximise liking
per group. Our approach employs (1) Genetic programming
(symbolic regression) and ensemble methods to generate
multiple diverse explanations of assessor liking
preferences with confidence information; (2)
statistical techniques to extrapolate using the
produced ensembles to unobserved regions of the flavor
space, and segment the assessors into groups which
either have the same propensity to like flavors, or are
driven by the same ingredients; and (3) two-objective
swarm optimization to identify flavors which are well
and consistently liked by a selected segment of
assessors.",
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affiliation = "CSAIL, MIT, 32 Vassar Street, D-540, Cambridge, MA,
USA",
- }
Genetic Programming entries for
Kalyan Veeramachaneni
Ekaterina (Katya) Vladislavleva
Una-May O'Reilly
Citations