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1.发明申请公开(公告)号：US20210406739A1
公开(公告)日：2021-12-30
申请号：US16915135
申请日：2020-06-29
摘要： There is a need for more effective and efficient predictive data analysis based at least in part on structured data. This need can be addressed by, for example, solutions for performing predictive data analysis using bidirectional encoder deep learning models that are configured to process structured data attributes. In one example, a method includes identifying a group of training structured data fields; generating a group of per-field tokenized values for each training structured data field; generating a bidirectional encoder deep learning model based at least in part on each group of per-field tokenized values for a training structured data field; and performing one or more prediction-based actions based at least in part on the trained bidirectional encoder deep learning model.
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2.发明授权公开(公告)号：US12131229B2
公开(公告)日：2024-10-29
申请号：US16915135
申请日：2020-06-29
摘要： There is a need for more effective and efficient predictive data analysis based at least in part on structured data. This need can be addressed by, for example, solutions for performing predictive data analysis using bidirectional encoder deep learning models that are configured to process structured data attributes. In one example, a method includes identifying a group of training structured data fields; generating a group of per-field tokenized values for each training structured data field; generating a bidirectional encoder deep learning model based at least in part on each group of per-field tokenized values for a training structured data field; and performing one or more prediction-based actions based at least in part on the trained bidirectional encoder deep learning model.
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