User Interface Optimization Using Genetic Programming with an Application to Landing Pages
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- @Article{journals/pacmhci/Salem17,
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author = "Paulo Salem",
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title = "User Interface Optimization Using Genetic Programming
with an Application to Landing Pages",
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journal = "Proceedings of the ACM on Human-Computer Interaction",
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year = "2017",
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volume = "1",
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number = "EICS",
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pages = "13:1--13:17",
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articleno = "13",
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month = jun,
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keywords = "genetic algorithms, genetic programming, fatigue
problem, interaction design, landing pages, user
interface generation, user interface optimisation",
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acmid = "3099583",
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publisher = "ACM",
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address = "New York, NY, USA",
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ISSN = "2573-0142",
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URL = "http://doi.acm.org/10.1145/3099583",
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DOI = "doi:10.1145/3099583",
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size = "17 pages",
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abstract = "The design of user interfaces (UIs), such as World
Wide Web pages, usually consists in a human designer
mapping one particular problem (e.g., the demands of a
customer) to one particular solution (i.e., the UI). In
this article, a technology based on Genetic Programming
is proposed to automate critical parts of the design
process. In this approach, designers are supposed to
define basic content elements and ways to combine them,
which are then automatically composed and tested with
real users by a genetic algorithm in order to find
optimised compositions. Such a strategy enables the
exploration of large design state-spaces in a
systematic manner, hence going beyond traditional A/B
testing approaches. In relation to similar techniques
also based on genetic algorithms, this system has the
advantage of being more general, providing the basis of
an overall programmatic UI design workflow, and of
calculating the fitness of solutions incrementally. To
illustrate and evaluate the approach, an experiment
based on the optimisation of landing pages is provided.
The empirical result obtained, though preliminary, is
statistically significant and corroborates the
hypothesis that the technique works.",
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notes = "Also known as \cite{Salem:2017:UIO:3120954.3099583}",
- }
Genetic Programming entries for
Paulo Salem
Citations