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公开(公告)号：US10298704B2
公开(公告)日：2019-05-21
申请号：US15336225
申请日：2016-10-27
Applicant: Microsoft Technology Licensing, LLC
Inventor： Arnab Nandi , Ryan D. Clark , Siddhartha Cingh Arora , Benjamin James Gaska
IPC: G06F16/29 , H04L29/06 , H04L29/08 , H04L29/12 , G06F16/9537
Abstract: The invention generally relates to systems and methods for determining geolocation for networks (e.g., IP addresses) for which accurate geolocation information in unknown. Various techniques are described for determining the physical location of networks by tracking user/device movement across different networks, and more particularly by tracking movement of particular users and/or devices from networks with known geolocation to networks with unknown geolocation. Aspects of the technology include using time and network address information (e.g., IP addresses) from user's queries and merging this information with known geolocation information to create new, high quality, geolocation mappings for previously unseen networks.
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公开(公告)号：US10887409B2
公开(公告)日：2021-01-05
申请号：US16386871
申请日：2019-04-17
Applicant: Microsoft Technology Licensing, LLC
Inventor： Arnab Nandi , Ryan D. Clark , Siddhartha Cingh Arora , Benjamin James Gaska
IPC: H04L29/08 , G06F16/29 , G06F16/9537 , H04L29/12 , H04L29/06
Abstract: The invention generally relates to systems and methods for determining geolocation for networks (e.g., IP addresses) for which accurate geolocation information in unknown. Various techniques are described for determining the physical location of networks by tracking user/device movement across different networks, and more particularly by tracking movement of particular users and/or devices from networks with known geolocation to networks with unknown geolocation. Aspects of the technology include using time and network address information (e.g., IP addresses) from user's queries and merging this information with known geolocation information to create new, high quality, geolocation mappings for previously unseen networks.
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公开(公告)号：US10805259B2
公开(公告)日：2020-10-13
申请号：US15798256
申请日：2017-10-30
Applicant: Microsoft Technology Licensing, LLC
Inventor： Ovidiu Dan , Vaibhav Girish Parikh , Maksym Bondarenko , Siddhartha Cingh Arora
Abstract: Generating an improved/more accurate geolocation database is provided. Given a dataset of reverse DNS hostnames for IP addresses, ground truth information, and a hierarchical geographical database, a machine learning classifier can be trained to extract and disambiguate location information from the reverse DNS hostnames of IP addresses and to apply machine learning algorithms to determine location candidates and to select a most probable candidate for a reverse DNS hostname based on a confidence score. The classifier can be used to generate an accurate geolocation database, or to provide accurate geolocation information as a service.
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公开(公告)号：US11700229B2
公开(公告)日：2023-07-11
申请号：US17015453
申请日：2020-09-09
Applicant: Microsoft Technology Licensing, LLC
Inventor： Ovidiu Dan , Vaibhav Girish Parikh , Maksym Bondarenko , Siddhartha Cingh Arora
IPC: H04L61/4511 , G06N20/00 , G06F16/29 , G06F16/25 , H04L61/5007 , H04L101/35 , H04L101/69
CPC classification number: H04L61/4511 , G06F16/258 , G06F16/29 , G06N20/00 , H04L61/5007 , H04L2101/35 , H04L2101/69
Abstract: Generating an improved/more accurate geolocation database is provided. Given a dataset of reverse DNS hostnames for IP addresses, ground truth information, and a hierarchical geographical database, a machine learning classifier can be trained to extract and disambiguate location information from the reverse DNS hostnames of IP addresses and to apply machine learning algorithms to determine location candidates and to select a most probable candidate for a reverse DNS hostname based on a confidence score. The classifier can be used to generate an accurate geolocation database, or to provide accurate geolocation information as a service.
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公开(公告)号：US20190007365A1
公开(公告)日：2019-01-03
申请号：US15798256
申请日：2017-10-30
Applicant: Microsoft Technology Licensing, LLC
Inventor： Ovidiu Dan , Vaibhav Girish Parikh , Maksym Bondarenko , Siddhartha Cingh Arora
CPC classification number: H04L61/1511 , G06F16/258 , G06F16/29 , G06N20/00 , H04L61/2007 , H04L61/305 , H04L61/609
Abstract: Generating an improved/more accurate geolocation database is provided. Given a dataset of reverse DNS hostnames for IP addresses, ground truth information, and a hierarchical geographical database, a machine learning classifier can be trained to extract and disambiguate location information from the reverse DNS hostnames of IP addresses and to apply machine learning algorithms to determine location candidates and to select a most probable candidate for a reverse DNS hostname based on a confidence score. The classifier can be used to generate an accurate geolocation database, or to provide accurate geolocation information as a service.
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Patent Agency Ranking
公开(公告)号：US20180124191A1
公开(公告)日：2018-05-03
申请号：US15336225
申请日：2016-10-27
Applicant: Microsoft Technology Licensing, LLC
Inventor： Arnab Nandi , Ryan D. Clark , Siddhartha Cingh Arora , Benjamin James Gaska
CPC classification number: H04L67/22 , G06F17/30241 , G06F17/3087 , H04L61/2007 , H04L67/18 , H04L67/42
Abstract: The invention generally relates to systems and methods for determining geolocation for networks (e.g., IP addresses) for which accurate geolocation information in unknown. Various techniques are described for determining the physical location of networks by tracking user/device movement across different networks, and more particularly by tracking movement of particular users and/or devices from networks with known geolocation to networks with unknown geolocation. Aspects of the technology include using time and network address information (e.g., IP addresses) from user's queries and merging this information with known geolocation information to create new, high quality, geolocation mappings for previously unseen networks.
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公开(公告)号：US12120260B2
公开(公告)日：2024-10-15
申请号：US17397467
申请日：2021-08-09
Applicant: Microsoft Technology Licensing, LLC
Inventor： Dragomir Dimitrov Yankov , Michael Robert Evans , Renzhong Wang , Senthil Kumar Palanisamy , Siddhartha Cingh Arora , Alex Jordan Yuter , Beibei Cheng , Wei Wu
IPC: H04M1/72451 , G06N3/049 , H04L51/046 , H04W4/029
CPC classification number: H04M1/72451 , G06N3/049 , H04L51/046 , H04W4/029
Abstract: Described herein are technologies related to generating a predicted routine of a user of a mobile computing device. Location entries generated by the mobile computing device are processed to generate visit entries, wherein the visit entries are representative of visits made by the user to places over several days. An input sequence of states is constructed based upon the visit entries, wherein each state has a place identifier assigned thereto, and further wherein each state corresponds to a time interval of predefined length. A predicted routine of the user is generated based upon the input sequence of states.
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公开(公告)号：US10397395B2
公开(公告)日：2019-08-27
申请号：US15597884
申请日：2017-05-17
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sudharssun Subramanian , Parmjeet Singh , Lakshmi Narayana Mummidi , Siddhartha Cingh Arora
IPC: H04M1/725 , H04W4/021 , H04W24/10 , H04W68/00 , H04L29/08 , H04W4/029 , H04W84/12 , H04W88/08 , H04W4/33
Abstract: Intent-based reminders are provided. A user is enabled to initiate a reminder request based on an intent to enter or leave a given location. In a geofence training process, a plurality of geofences are created for plotting a path and subsequently tracking the user's traversal of the path for inferring the user's intent to depart or enter the location. A signal strength of a WLAN is recorded at each geofence. As the user traverses the path, a determination is made as to whether a predetermined percentage of the geofences is triggered in a sequential order by comparing the signal strength of the WLAN against the recorded WLAN signal strengths at the geofences. In some examples, signal strengths of neighboring WLANs are recorded and used to filter out false triggers. When a determination is made that the user's intent is to depart or enter the location, a reminder is provided.
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公开(公告)号：US20190245936A1
公开(公告)日：2019-08-08
申请号：US16386871
申请日：2019-04-17
Applicant: Microsoft Technology Licensing, LLC
Inventor： Arnab Nandi , Ryan D. Clark , Siddhartha Cingh Arora , Benjamin James Gaska
IPC: H04L29/08 , G06F16/9537 , G06F16/29 , H04L29/12 , H04L29/06
CPC classification number: H04L67/22 , G06F16/29 , G06F16/9537 , H04L61/2007 , H04L67/18 , H04L67/42
Abstract: The invention generally relates to systems and methods for determining geolocation for networks (e.g., IP addresses) for which accurate geolocation information in unknown. Various techniques are described for determining the physical location of networks by tracking user/device movement across different networks, and more particularly by tracking movement of particular users and/or devices from networks with known geolocation to networks with unknown geolocation. Aspects of the technology include using time and network address information (e.g., IP addresses) from user's queries and merging this information with known geolocation information to create new, high quality, geolocation mappings for previously unseen networks.
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公开(公告)号：US20180338031A1
公开(公告)日：2018-11-22
申请号：US15597884
申请日：2017-05-17
Applicant: Microsoft Technology Licensing, LLC
Inventor： Sudharssun Subramanian , Parmjeet Singh , Lakshmi Narayana Mummidi , Siddhartha Cingh Arora
CPC classification number: H04M1/72572 , H04L67/22 , H04W4/021 , H04W4/022 , H04W4/029 , H04W4/33 , H04W24/10 , H04W68/005 , H04W84/12 , H04W88/08
Abstract: Intent-based reminders are provided. A user is enabled to initiate a reminder request based on an intent to enter or leave a given location. In a geofence training process, a plurality of geofences are created for plotting a path and subsequently tracking the user's traversal of the path for inferring the user's intent to depart or enter the location. A signal strength of a WLAN is recorded at each geofence. As the user traverses the path, a determination is made as to whether a predetermined percentage of the geofences is triggered in a sequential order by comparing the signal strength of the WLAN against the recorded WLAN signal strengths at the geofences. In some examples, signal strengths of neighboring WLANs are recorded and used to filter out false triggers. When a determination is made that the user's intent is to depart or enter the location, a reminder is provided.
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