- 专利标题: Machine learning system and method for determining or inferring user action and intent based on screen image analysis
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申请号: US17318032申请日: 2021-05-12
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公开(公告)号: US11704898B2公开(公告)日: 2023-07-18
- 发明人: Ali Jelveh
- 申请人: M37 Inc.
- 申请人地址: US CA San Francisco
- 专利权人: M37 INC.
- 当前专利权人: M37 INC.
- 当前专利权人地址: US CA San Francisco
- 代理机构: Amin, Turocy & Watson, LLP
- 主分类号: G06V10/778
- IPC分类号: G06V10/778 ; G06K9/62 ; G06N3/084 ; G06N20/00 ; G06F18/21 ; G06F18/40 ; G06T13/40 ; G06N3/006 ; G06N7/01
摘要:
System(s) and method(s) that analyze image data associated with a computing screen operated by a user, and learns the image data (e.g., using pattern recognition, historical information analysis, user implicit and explicit training data, optical character recognition (OCR), video information, 360°/panoramic recordings, and so on) to concurrently glean information regarding multiple states of user interaction (e.g., analyzing data associated with multiple applications open on a desktop, mobile phone or tablet). A machine learning model is trained on analysis of graphical image data associated with screen display to determine or infer user intent. An input component receives image data regarding a screen display associated with user interaction with a computing device. An analysis component employs the model to determine or infer user intent based on the image data analysis; and an action component provisions services to the user as a function of the determined or inferred user intent. In an implementation, a gaming component gamifies interaction with the user in connection with explicitly training the model.
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