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公开(公告)号：US20190394202A1
公开(公告)日：2019-12-26
申请号：US16560622
申请日：2019-09-04
发明人： John Jun Wu , John S. Yi
摘要： Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.
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公开(公告)号：US11301572B2
公开(公告)日：2022-04-12
申请号：US16990404
申请日：2020-08-11
发明人： John Jun Wu , John S. Yi
IPC分类号： G06F21/00 , G06F21/60 , H04L29/06 , G06F21/62 , G06N20/00 , G06F21/74 , G06F21/85 , H04W12/088 , G06N5/04 , G06N5/02
摘要： Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.
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公开(公告)号：US20220337592A1
公开(公告)日：2022-10-20
申请号：US17717591
申请日：2022-04-11
发明人： John Jun Wu , John S. Yi
IPC分类号： H04L9/40
摘要： Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.
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公开(公告)号：US20200372161A1
公开(公告)日：2020-11-26
申请号：US16990404
申请日：2020-08-11
发明人： John Jun Wu , John S. Yi
摘要： Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.
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公开(公告)号：US20170353463A1
公开(公告)日：2017-12-07
申请号：US15616668
申请日：2017-06-07
发明人： John Jun Wu , John S. Yi
摘要： Various embodiments provide an approach to controlled access to online content. Such control may be based on a multitude of factors including but not limited to website content, profile for the person consuming the data. In operation, machine-learning techniques are used to classify the websites based on community and social media inputs, crowd-sourced data, as well as access rules implemented by parents or system administrators. Feedback from users/admins of the system, including the instances of allowed or denied access to websites, in conjunction with other relevant parameters, is used for iterative machine-learning techniques. Embodiments may also allow for real, or near real-time, approval or denial of access to websites by registered admins.
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