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案件記録

PERSONALIZED DOCUMENT FIELD PREDICTION BASED ON LEARNING FROM USER FEEDBACK

発明審査中
1閲覧数
20請求項 · 3 独立
§ Ⅰ

案件概要

発明者

Max STEPIN; Mohsen SARDARI; Gaurav TANDON; Changlin ZHANG; Nakul CHAKRAPANI

IPC分類

G6V 30/412G6F 16/11G6V 30/414

CPC分類

G6V30/412G6F16/116G6V30/414

Particular embodiments relate to personalized document field prediction based on user behavior and feature generation. Specifically, various embodiments have the technical effect of improved accuracy with respect to field/entity value prediction (e.g., predicting that the amount due is X via a Gradient Boosting Model) relative to document processing technologies by learning through user behavior data or feedback (e.g., through continuous reinforcement learning from human feedback (RLHF)). This is at least partially because of the technical solution of accessing or generating unique features from one or more documents previously used by a user.

原文(中国語)

Particular embodiments relate to personalized document field prediction based on user behavior and feature generation. Specifically, various embodiments have the technical effect of improved accuracy with respect to field/entity value prediction (e.g., predicting that the amount due is X via a Gradient Boosting Model) relative to document processing technologies by learning through user behavior data or feedback (e.g., through continuous reinforcement learning from human feedback (RLHF)). This is at least partially because of the technical solution of accessing or generating unique features from one or more documents previously used by a user.

外部リソース