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公开(公告)号：US20240111771A1
公开(公告)日：2024-04-04
申请号：US17959520
申请日：2022-10-04
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Elijah Hall , Edmond J. Abrahamian , Ana Armenta , Andrew Campbell , Jean Luo , Prince Paulraj
IPC: G06F16/2455 , G06F16/28
CPC classification number: G06F16/2455 , G06F16/283
Abstract: A processing system may apply a community detection process to a feature graph database to identify a plurality of communities of features, the feature graph database comprising: a plurality of objects, each associated with one of a feature or a concept, and a plurality of relationships between the plurality of objects. Next, the processing system may label a first plurality of features of the feature graph database with at least a first community label, where the first plurality of features comprises features of at least a first community of the plurality of communities. The processing system may then obtain a search associated with at least one feature of the feature graph database, where the at least one feature is a part of the at least the first plurality of features of the at least the first community, and provide the first plurality of features in response to the search.
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公开(公告)号：US11943386B2
公开(公告)日：2024-03-26
申请号：US17566886
申请日：2021-12-31
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Elijah Hall , Prince Paulraj , Ana Armenta , Surya Murali
CPC classification number: H04M15/58 , G06N5/022 , H04M3/2281 , H04M15/41 , H04M15/47
Abstract: A processing system may maintain a communication graph that includes nodes representing a plurality of phone numbers including a first phone number and edges between the nodes representing a plurality of communications between the plurality of phone numbers and may generate at least one vector via a graph embedding process applied to the communication graph, the at least one vector representing features of at least a portion of the communication graph. The processing system may then apply the at least one vector to a prediction model that is implemented by the processing system and that is configured to predict whether the first phone number is associated with a type of network activity associated with a telecommunication network and may implement a remedial action in response to an output of the prediction model indicating that the first phone number is associated with the type of network activity.
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公开(公告)号：US20230216967A1
公开(公告)日：2023-07-06
申请号：US17566905
申请日：2021-12-31
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Surya Murali , Edmond J. Abrahamian , Ana Armenta , Prince Paulraj , Elijah Hall
CPC classification number: H04M15/47 , H04W8/26 , H04M3/2281 , H04M3/2218 , G06N20/00
Abstract: A processing system may maintain a relationship graph that includes nodes and edges representing phone numbers and device identifiers having associations with the phone numbers. The processing system may obtain an identification of a first phone number or a first device identifier for a fraud evaluation and extract features from the relationship graph associated with at least one of the first phone number or the first device identifier. The plurality of features may include one or more device identifiers associated with the first phone number, or one or more phone numbers associated with the first device identifier. The processing system may then apply the features to a prediction model that is implemented by the processing system and that is configured to output a fraud risk value of the first phone number or the first device identifier and implement at least one remedial action in response to the fraud risk value.
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Patent Agency Ranking
公开(公告)号：US20230153873A1
公开(公告)日：2023-05-18
申请号：US17529964
申请日：2021-11-18
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Qiuying Jiang , Ana Armenta , Prince Paulraj , Jean Luo
CPC classification number: G06Q30/04 , G06F16/2379
Abstract: Aspects of the subject disclosure may include, for example, obtaining first information indicative of a first change to a first aspect of a user account; applying some or all of the first information to a first model to determine a first score associated with the first change; aggregating the first score with one or more first prior scores associated with one or more prior changes to the first aspect of the user account, resulting in a first aggregate score; obtaining second information indicative of a second change to a second aspect of the user account; applying some or all of the second information to a second model, that is different from the first model, to determine a second score associated with the second change; aggregating the second score with one or more second prior scores associated with one or more prior changes to the second aspect of the user account, resulting in a second aggregate score; and storing the first aggregate score and the second aggregate score in a database. Other embodiments are disclosed.
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公开(公告)号：US20230029312A1
公开(公告)日：2023-01-26
申请号：US17382746
申请日：2021-07-22
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Prince Paulraj , Arun Luthra , Ana Armenta , Jean Luo
Abstract: To detect multiple suspicious patterns while at the same time keeping the number of model parameters low, a learned aggregation model is used to distinguish suspiciously similar applications from unrelated applications.
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公开(公告)号：US11561933B2
公开(公告)日：2023-01-24
申请号：US17220260
申请日：2021-04-01
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Paul Ireifej , Mohammad Omar Khalid Mirza , Prince Paulraj , Heather Wighton , Christopher Kim , Stephen Grandinetti , Mger Babayan
Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.
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公开(公告)号：US20220383151A1
公开(公告)日：2022-12-01
申请号：US17331225
申请日：2021-05-26
Applicant: AT&T Intellectual Property I, L.P. , AT&T Mobility II LLC
Inventor： Yukun Zeng , Prince Paulraj , Sherri Rogers , Scott Alexander , Shilpi Harpavat , Shreyash Taywade , Aubryn Lewis , Cameron Dunn , Sandeep David Golkonda , Roli Arora
Abstract: Aspects of the subject disclosure may include, for example, obtaining roaming agreement data related to roaming agreements that are between a wireless provider and a respective one of a plurality of wireless roaming providers; obtaining, for each wireless subscriber of the wireless provider, respective roaming usage data, all of the respective roaming usage data comprising collective roaming usage data; training, based upon the collective roaming usage data, a set of one or more models, the one or more models comprising one or more statistical models, one or more machine learning models, or any combination thereof, the one or more models being trained with multiple iterations of feedback loops, and the training resulting in one or more trained models; estimating for each wireless subscriber, based upon the one or more trained models, respective projected location information for a future time, all of the respective projected location information comprising collective projected location information; obtaining, for each of a plurality of wireless coverage areas of the plurality of wireless roaming providers, respective real-time network quality measurement data, all of the respective real-time network quality measurement data comprising collective real-time network quality measurement data; modeling a plurality of scenarios for the future time based upon the roaming agreement data, based upon the collective real-time network quality measurement data and based upon the collective projected location information, each of the scenarios identifying for each of a plurality of projected future wireless roaming subscribers a respective one of the wireless roaming providers to communicate with at the future time, each of the scenarios further identifying a respective cost to the wireless provider, and the modeling being performed via use of a plurality of model constraints; selecting from the scenarios, as a selected scenario, a scenario that has associated therewith a lowest total cost to the wireless provider also satisfying one or more of the plurality of model constraints based upon the collective roaming agreement data; and sending recommendations, to a plurality of steering mechanisms, in order to implement the selected scenario. Other embodiments are disclosed.
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公开(公告)号：US20210173822A1
公开(公告)日：2021-06-10
申请号：US16782754
申请日：2020-02-05
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Prince Paulraj , Shilpi Harpavat , Weiping Liu , Shreyash Taywade , Arjun Coimbatore Nagarasan , Yukun Zeng , Prabhu Gururaj
Abstract: In another example, a device includes a processor and a computer-readable medium storing instructions which, when executed by the processor, cause the processor to perform operations. The operations include acquiring a plurality of data items from a plurality of data sources, wherein the at least two data sources data sources of the plurality of data sources are maintained by different entities, normalizing attributes of the plurality of data items, using a first machine learning technique, matching at least two data items of the plurality of data items to form a grouping, wherein the matching is based on similarities observed in the attributes of the at least two data items subsequent to the normalizing, and creating a single profile for an individual associated with the at least two data items, based on the grouping, wherein the single profile consolidates the attributes of the at least two data items.
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