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公开(公告)号:US20180107936A1
公开(公告)日:2018-04-19
申请号:US15476487
申请日:2017-03-31
Applicant: Intel Corporation
Inventor: Rita Chattopadhyay , Kalpana A. Algotar , Ali Ashrafi , John Pilkin
CPC classification number: G06N7/005 , A63B24/0062 , G16H20/30 , G16H50/20 , G16H50/30
Abstract: A disclosed example method to predict an injury for a target player on a target date includes determining a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determining a second probability of injury of the target player based on injuries of the target player; determining a third probability of injury of the target player based on the first probability of injury of the target player and the second probability of injury of the target player; and generating, by executing an instruction with the processor, a report of a predicted probability of injury of the target player for the target date based on the third probability of injury of the target player.
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公开(公告)号:US10957450B2
公开(公告)日:2021-03-23
申请号:US15396075
申请日:2016-12-30
Applicant: Intel Corporation
Inventor: Rita Chattopadhyay , Kalpana A. Algotar , Amith Harsha , Ravindra V. Narkhede
Abstract: Systems, apparatuses and methods may provide for technology that assigns confidence levels to data bins containing similarity data and length of stay data, wherein the similarity data and the length of stay data correspond to a plurality of previous admissions. Additionally, the confidence levels may be weighted based on a distribution metric that assigns higher weights to denser regions. A length of stay of a target admission may be predicted based on the weighted confidence levels.
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公开(公告)号:US20220129776A1
公开(公告)日:2022-04-28
申请号:US17342197
申请日:2021-06-08
Applicant: Intel Corporation
Inventor: Rita Chattopadhyay , Kalpana A. Algotar , Ali Ashrafi , John Pilkin
Abstract: A disclosed example method to predict an injury for a target player on a target date includes determining a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determining a second probability of injury of the target player based on injuries of the target player; determining a third probability of injury of the target player based on the first probability of injury of the target player and the second probability of injury of the target player; and generating, by executing an instruction with the processor, a report of a predicted probability of injury of the target player for the target date based on the third probability of injury of the target player.
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公开(公告)号:US11049031B2
公开(公告)日:2021-06-29
申请号:US15476487
申请日:2017-03-31
Applicant: Intel Corporation
Inventor: Rita Chattopadhyay , Kalpana A. Algotar , Ali Ashrafi , John Pilkin
Abstract: A disclosed example method to predict an injury for a target player on a target date includes determining a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determining a second probability of injury of the target player based on injuries of the target player; determining a third probability of injury of the target player based on the first probability of injury of the target player and the second probability of injury of the target player; and generating, by executing an instruction with the processor, a report of a predicted probability of injury of the target player for the target date based on the third probability of injury of the target player.
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公开(公告)号:US10909335B2
公开(公告)日:2021-02-02
申请号:US16062105
申请日:2015-12-22
Applicant: Intel Corporation
Inventor: Guang-He Lee , Kalpana A. Algotar , Shao-Wen Yang , Addicam V. Sanjay
Abstract: A set of samples are returned by radio frequency identifier (RFID) reader corresponding to the readings of signals emitted from a particular RFID tag, each sample including a respective set of features identifying values of the attributes of the signals as detected. At least some of the features are provided as inputs to a random forest of decision trees, each providing a prediction that the particular RFID tag is located in one of a plurality of defined zones in a particular environment. From outputs of the plurality of decision trees based on the set of samples, it can be determined that the particular RFID tag is located in a particular one of the plurality of zones at a first instance in time.
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公开(公告)号:US20180373906A1
公开(公告)日:2018-12-27
申请号:US16062105
申请日:2015-12-22
Applicant: Intel Corporation
Inventor: Guang-He Lee , Kalpana A. Algotar , Shao-Wen Yang , Addicam V. Sanjay
Abstract: A set of samples are returned by radio frequency identifier (RFID) reader corresponding to the readings of signals emitted from a particular RFID tag, each sample including a respective set of features identifying values of the attributes of the signals as detected. At least some of the features are provided as inputs to a random forest of decision trees, each providing a prediction that the particular RFID tag is located in one of a plurality of defined zones in a particular environment. From outputs of the plurality of decision trees based on the set of samples, it can be determined that the particular RFID tag is located in a particular one of the plurality of zones at a first instance in time.
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公开(公告)号:US20170177739A1
公开(公告)日:2017-06-22
申请号:US14979300
申请日:2015-12-22
Applicant: Intel Corporation
Inventor: Kalpana A. Algotar , Addicam V. Sanjay
CPC classification number: G06F16/9024 , G06F16/9014 , G06N5/02 , G06N5/04 , G06N20/00
Abstract: Techniques for prediction using multimap is described herein. The method for multimap prediction can include generating a user profile graph in the memory device based on user action input received at an input device. The method for multimap prediction can also include matching a user profile graph stored in the memory device to a subgraph of a multimap graph, both comprising nodes and edges, wherein each node indicates at least one of an activity input and a keyword. The method can include providing access to a multimap prediction in the memory device based on the user action input and the subgraph of the multimap graph.
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