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公开(公告)号：US20140180974A1
公开(公告)日：2014-06-26
申请号：US13725561
申请日：2012-12-21
发明人： Matthew Bochner Kennel , Hua Li , Larry Peranich
IPC分类号： G06N99/00
CPC分类号： G06Q30/0609 , G06N7/005 , G06Q20/403 , G06Q40/025
摘要： The current subject matter describes scoring of transactions associated with a profiling entity so as to determine risk associated with the transactions. Data characterizing at least one new transaction can be received. A latent dirichlet allocation (LDA) model trained on historical data can be obtained. Based on new words in the received data, the LDA model can update a topic probability mixture vector. Based on the updated topic probability mixture vector, numerical values of one or more predictive features can be calculated. Based on the numerical values of the one or more predicted features, the at least one transaction in the received data can be scored. Related apparatus, systems, techniques and articles are also described.
摘要翻译： 目前的主题描述了与分析实体相关联的交易的评分，以便确定与交易相关联的风险。 可以接收表征至少一个新事务的数据。 可以获得对历史数据训练的潜在狄里克雷分配（LDA）模型。 基于接收数据中的新词，LDA模型可以更新主题概率混合向量。 基于更新的主题概率混合向量，可以计算一个或多个预测特征的数值。 基于一个或多个预测特征的数值，可以对接收到的数据中的至少一个事务进行评分。 还描述了相关设备，系统，技术和物品。
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公开(公告)号：US20200151628A1
公开(公告)日：2020-05-14
申请号：US16681501
申请日：2019-11-12
发明人： Scott M. Zoldi , Larry Peranich , Jehangir Athwal , Uwe Mayer , Sajama
摘要： A computer-implemented method for technologically improving a computer-implemented machine-learning model, the method comprising receiving, by a model, at least a first data record; generating a first score representing a first likelihood that the first data record is associated with a first classification, in response to feedback received from one or more data sources communicating with at least one computing system on which the model is implemented; generating a second score to represent a second likelihood that the first data record is associated with the first classification, in response to the first score being higher than a threshold value.
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