Visualizing Products and Consumers: A Gestalt Theory Inspired Method
Created by W.Langdon from
gp-bibliography.bib Revision:1.7989
- @InCollection{Lobos2019,
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author = "Claudio Sanhueza Lobos and Natalie Jane {de Vries} and
Mario Inostroza-Ponta and Regina Berretta and
Pablo Moscato",
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title = "Visualizing Products and Consumers: A Gestalt Theory
Inspired Method",
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booktitle = "Business and Consumer Analytics: New Ideas",
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publisher = "Springer International Publishing",
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year = "2019",
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editor = "Pablo Moscato and Natalie Jane {de Vries}",
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chapter = "16",
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pages = "661--689",
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keywords = "genetic algorithms, genetic programming, Memetic
algorithm, Customer Churn, Effective visualizations,
Quadratic assignment problem",
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isbn13 = "978-3-030-06222-4",
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URL = "http://hdl.handle.net/1959.13/1460520",
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DOI = "doi:10.1007/978-3-030-06222-4_16",
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abstract = "Motivated by the ability that visualisations have for
explaining complex relationships, we revisit an
alternative and efficient algorithm for visualizing
relationships between objects. QAPgrid was proposed to
solve the problem of allocating objects in a grid. The
algorithm uses as its mathematical model the
NP-hardNP-hard Quadratic assignment problem quadratic
assignment Assignment Problem. We implemented an
efficient AlgorithmmemeticMemetic algorithmMemetic
Algorithm for solving the layout optimization problem.
The algorithm has been previously tested on a variety
of datasets with good results. In this chapter, we
explore the algorithm's potential for analysing social
networks. In particular, we examined the collaboration
network created around the artificial world of the
MarveluniverseMarvel Universe comic books. We show how
the algorithm can generate accurate and informative
visualizations for analysing complex graphs.
Furthermore, to demonstrate an alternative use of the
algorithm, we analyse and visualize products (wines)
and customers (telecom clients). In doing so, we show
how the algorithm is suitable for the analysis of
different types of objects organized as a network.",
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notes = "also known as \cite{DBLP:books/sp/19/LobosVIBM19}",
- }
Genetic Programming entries for
Claudio Sanhueza Lobos
Natalie Jane de Vries
Mario Inostroza-Ponta
Regina Berretta
Pablo Moscato
Citations