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Applied artificial intelligence technology for processing trade data to detect patterns indicative of potential trade spoofing
Applied artificial intelligence technology for processing trade data to detect patterns indicative of potential trade spoofing
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机译:应用人工智能技术处理贸易数据以检测指示潜在贸易欺骗的模式
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摘要
Various techniques are described for using machine-learning artificial intelligence to improve how trading data can be processed to detect improper trading behaviors such as trade spoofing. In an example embodiment, semi-supervised machine learning is applied to positively labeled and unlabeled training data to develop a classification model that distinguishes between trading behavior likely to qualify as trade spoofing and trading behavior not likely to qualify as trade spoofing. Also, clustering techniques can be employed to segment larger sets of training data and trading data into bursts of trading activities that are to be assessed for potential trade spoofing status.
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