From Business Curated Products to Algorithmically Generated

Created by W.Langdon from gp-bibliography.bib Revision:1.8656

@InProceedings{Kalinichenko:2020:evostarLBA,

• author = "Vera Kalinichenko and Garima Garg",
• title = "From Business Curated Products to Algorithmically Generated",
• booktitle = "Evostar 2020 Late breaking abstracts",
• year = "2020",
• editor = "Antonio M. Mora and Anna I. Esparcia-Alcazar",
• pages = "6--9",
• address = "Online",
• month = "15-17 " # apr,
• organisation = "Species",
• keywords = "genetic algorithms, genetic programming, FabFitFun, e-commence, Amazon marketplace, optimal solutions, novelty, classifier, Generate Synthetic Data",
• URL = "https://arxiv.org/abs/2005.07235",
• size = "4 pages",
• abstract = "FabFitFun we have developed a bundle of machine learning models that enabled us algorithmically assemble future boxes that are shipped to our members. FabFitFun is a technology and e-commence startup that works with small vendors to discover cool products in a similar fashion to Amazon marketplace. The team of data scientists use our historical data which includes details of our customers and products we have sold and are planning to sell, programmatically discover new products. We use classical machine learning supervised models to classify our products and latest technologies like genetic programming, linear optimization to help business to curate products to members in a new era. Genetic programming allows us to spot repetitive features for our supervised learning models, provide product diversity via measuring how far away a newly generated collection of products are from the historically seen and the optimal solution. Our paper demonstrates novel way to evaluate algorithmically created boxes using Sharpe Ratio concept from finance. Thus, we discover novel products based on the distance threshold from the optimal solutions and adapted way to evaluate boxes with Sharpe Scores. Use genetic programming to generate synthetic data, provide diversity, novelty across our products",

}

Genetic Programming entries for Vera Kalinichenko Garima Garg

Citations