DATA SET CREATION WITH CROWD-BASED REINFORCEMENT

摘要

A system and method for creation and expansion of high quality data set collections for training of machine learning algorithms via crowdsourced curation that utilizes a data marketplace which incentivizes data gatherers, publishers, and users to contribute to the creation of a vast resource of reliable data set collections. Data is automatically ingested from disparate sources and autonomously checked for data quality, provenance, and cyber-risks and subsequently given a reputation score. Data stewards curate a queue of low scoring real data as well as synthetically generated data. All reputable data is stored for user consumption and further iterative data generation.