公开(公告)号：US20230315996A1

公开(公告)日：2023-10-05

申请号：US18206296

申请日：2023-06-06

申请人： American Express Travel Related Services Company, Inc.

发明人： Ravi BATRA ,  Sandeep BOSE ,  Mario FRAGOSO ,  Ravneet GHUMAN ,  Madhu Sudan Reddy GUDUR ,  Suraj MADNANI ,  Curtis T. MERRYWEATHER ,  Ravi VARMA ,  Vinod YADAV

IPC分类号： G06F40/30 ,  G06F16/95 ,  G06N5/045 ,  G06N20/00 ,  G06F40/295

CPC分类号： G06F40/30 ,  G06F16/95 ,  G06N5/045 ,  G06N20/00 ,  G06F40/295 ,  G06Q40/02

摘要： Systems and methods for identifying data of interest are disclosed. The system may retrieve unstructured data from an internet data source via an alert system or RSS feed. The system may input the unstructured data into various models and scoring systems to determine whether the data is of interest. The models and scoring systems may be executed in order or in parallel. For example, the system may input the unstructured data into a Naïve Bayes machine learning model, a long short-term memory (LSTM) machine learning model, a named entity recognition (NER) model, a semantic role labeling (SRL) model, a sentiment scoring algorithm, and/or a gradient boosted regression tree (GBRT) machine learning model. Based on determining that the unstructured data is of interest, a data alert may be generated and transmitted for manual review or as part of an automated decisioning process.

公开(公告)号：US20220391593A1

公开(公告)日：2022-12-08

申请号：US17679498

申请日：2022-02-24

申请人： American Express Travel Related Services Company, Inc.

发明人： Ravi BATRA ,  Sandeep BOSE ,  Mario FRAGOSO ,  Ravneet GHUMAN ,  Madhu Sudan Reddy GUDUR ,  Suraj MADNANI ,  Curtis T. MERRYWEATHER ,  Ravi VARMA ,  Vinod YADAV

IPC分类号： G06F40/30 ,  G06F16/95 ,  G06N5/04 ,  G06N20/00 ,  G06F40/295

摘要： Systems and methods for identifying data of interest are disclosed. The system may retrieve unstructured data from an internet data source via an alert system or RSS feed. The system may input the unstructured data into various models and scoring systems to determine whether the data is of interest. The models and scoring systems may be executed in order or in parallel. For example, the system may input the unstructured data into a Naive Bayes machine learning model, a long short-term memory (LSTM) machine learning model, a named entity recognition (NER) model, a semantic role labeling (SRL) model, a sentiment scoring algorithm, and/or a gradient boosted regression tree (GBRT) machine learning model. Based on determining that the unstructured data is of interest, a data alert may be generated and transmitted for manual review or as part of an automated decisioning process.