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1.发明授权公开(公告)号：US11803797B2
公开(公告)日：2023-10-31
申请号：US17512150
申请日：2021-10-27
IPC分类号： G06Q10/0635 , G06Q10/107 , G06N20/20 , G06F40/284 , G06F18/2433
CPC分类号： G06Q10/0635 , G06F18/2433 , G06F40/284 , G06N20/20 , G06Q10/107
摘要： Systems, methods, and other embodiments associated with a machine learning system that monitors and detects health and safety risks in electronic correspondence related to a target field are described. In one embodiment, a method includes monitoring email communications over a network to identify an email associated with a target field. A machine learning classifier is initiated that is configured to classify text from the email with a risk as being related to a safety risk or a non-risk. The machine learning classifier generates a probability risk value that the email is related to a safety risk and labels the email as safety risk or non-risk based at least in part on the probability risk value indicating that the email is a safety risk. An electronic notice is generated and transmitted to a remote device in response to the email being labeled as being safety risk to provide an alert.
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公开(公告)号：US11615361B2
公开(公告)日：2023-03-28
申请号：US17307163
申请日：2021-05-04
摘要： Systems, methods, and other embodiments associated with detecting severity levels of risk in an electronic correspondence are described. In one embodiment, a method includes inputting, into a memory, a target electronic correspondence that has been classified as being litigious by a machine learning classifier. An artificial intelligence rule-based technique is applied to the target electronic correspondence that identifies high and medium risk level keywords. The technique is also configured to generate a litigious score based on a sum of term frequencies-inverse document frequencies using the remaining keywords. An electronic notice is transmitted to a remote computer over a communication network that identifies the target electronic correspondence and the level of litigation risk.
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