Collaborative Analytics with Genetic Programming for Workflow Recommendation

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Chong:2013:SMC,
  author =       "Chee Seng Chong and Tianyou Zhang and 
                 Kee Khoon Lee and Gih Guang Hung and Bu-Sung Lee",
  title =        "Collaborative Analytics with Genetic Programming for
                 Workflow Recommendation",
  booktitle =    "IEEE International Conference on Systems, Man, and
                 Cybernetics (SMC 2013)",
  year =         "2013",
  month =        oct,
  pages =        "657--662",
  keywords =     "genetic algorithms, genetic programming, Work flow
                 recommendation, collaborative analytics",
  DOI =          "doi:10.1109/SMC.2013.117",
  size =         "6 pages",
  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.",
  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