Collaborative Analytics with Genetic Programming for Workflow Recommendation
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Chong:2013:SMC,
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author = "Chee Seng Chong and Tianyou Zhang and
Kee Khoon Lee and Gih Guang Hung and Bu-Sung Lee",
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title = "Collaborative Analytics with Genetic Programming for
Workflow Recommendation",
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booktitle = "IEEE International Conference on Systems, Man, and
Cybernetics (SMC 2013)",
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year = "2013",
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month = oct,
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pages = "657--662",
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keywords = "genetic algorithms, genetic programming, Work flow
recommendation, collaborative analytics",
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DOI = "doi:10.1109/SMC.2013.117",
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size = "6 pages",
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abstract = "Formulation of appropriate data analytics workflows
requires intricate knowledge and rich experiences of
data analytics experts. This problem is further
compounded by continuous advancement and improvement in
analytical algorithms. In this paper, a generic
non-domain specific solution for the creation of
appropriate work-flows targeted at supervised learning
problems is proposed. Our adaptive work flow
recommendation engine based on collaborative analytics
matches analytics needs with relevant work flows in
repository. It is capable of picking workflows with
better performance as compared to randomly selected
work-flows. The recommendation engine is now augmented
by a work-flow optimiser that applies genetic
programming to further improve the recommended
workflows through iterative evolution, leading to
better alternative workflows. This unique Collaborative
Analytics Recommender System is tested on seven UCI
benchmark datasets. It is shown that the final
workflows produced by the system could closely
approximate, in terms of accuracy, the best workflows
that analytics experts could possibly design.",
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notes = "Terence Hung = Gih Guang Hung. Bu-Sung Lee = Francis
Lee. Also known as \cite{6721870}",
- }
Genetic Programming entries for
Chee Seng Chong
Tianyou Zhang
Kee Khoon Lee
Terence Hung
Bu Sung Lee
Citations