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公开(公告)号：US20200302018A1
公开(公告)日：2020-09-24
申请号：US16362187
申请日：2019-03-22
Applicant: ServiceNow, Inc.
Inventor： Omer Anil Turkkan , Firat Karakusoglu , Sriram Palapudi
IPC: G06F17/27
Abstract: Systems and methods are provided to compare a target sample of text to a set of textual records, each textual record including a sample of text and an indication of one or more segments of text within the sample of text. Semantic similarity values between the target sample of text and each of the textual records are determined. Determining a particular semantic similarity value between the target sample of text and a particular textual record of the corpus includes: (i) determining individual semantic similarity values between the target sample of text and each of the segments of text indicated by the particular textual record, and (ii) generating the particular semantic similarity value between the target sample of text and the particular textual record based on the individual semantic similarity values. A textual record is then selected based on the semantic similarities.
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公开(公告)号：US12265796B2
公开(公告)日：2025-04-01
申请号：US17579028
申请日：2022-01-19
Applicant: ServiceNow, Inc.
Inventor： Maxim Naboka , Edwin Sapugay , Sagar Davasam Suryanarayan , Anil Kumar Madamala , Rammohan Narendula , Omer Anil Turkkan , Aniruddha Madhusudan Thakur , Sriram Palapudi
IPC: G06F40/40 , G06F21/62 , G06F40/284
Abstract: A natural language understanding (NLU) framework includes a lookup source framework, which enables a lookup source system to be defined having one or more lookup sources. Each lookup source of the lookup source system includes a respective source data representation that is compiled from respective source data. For example, a source data representation may include source data arranged in a finite state transducer (IFST) structure as a set of finite-state automata (FSA) states, wherein each state is associated with a token that represents underlying source data. Different producers can be applied during compilation of a source data representation to derive additional states within the source data representation from the source data. Certain states of the source data representation that contain sensitive data can be selectively protected through encryption and/or obfuscation, while other portions of the source data representation that are not sensitive may remain in clear-text form.
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公开(公告)号：US20220229998A1
公开(公告)日：2022-07-21
申请号：US17579028
申请日：2022-01-19
Applicant: ServiceNow, Inc.
Inventor： Maxim Naboka , Edwin Sapugay , Sagar Davasam Suryanarayan , Anil Kumar Madamala , Rammohan Narendula , Omer Anil Turkkan , Aniruddha Madhusudan Thakur , Sriram Palapudi
IPC: G06F40/40 , G06F40/284 , G06F21/62
Abstract: A natural language understanding (NLU) framework includes a lookup source framework, which enables a lookup source system to be defined having one or more lookup sources. Each lookup source of the lookup source system includes a respective source data representation that is compiled from respective source data. For example, a source data representation may include source data arranged in a finite state transducer (IFST) structure as a set of finite-state automata (FSA) states, wherein each state is associated with a token that represents underlying source data. Different producers can be applied during compilation of a source data representation to derive additional states within the source data representation from the source data. Certain states of the source data representation that contain sensitive data can be selectively protected through encryption and/or obfuscation, while other portions of the source data representation that are not sensitive may remain in clear-text form.
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公开(公告)号：US20220012431A1
公开(公告)日：2022-01-13
申请号：US17448667
申请日：2021-09-23
Applicant: ServiceNow, Inc.
Inventor： Omer Anil Turkkan , Firat Karakusoglu , Sriram Palapudi
IPC: G06F40/30 , G06F40/284 , G06F40/205
Abstract: Systems and methods are provided to compare a target sample of text to a set of textual records, each textual record including a sample of text and an indication of one or more segments of text within the sample of text. Semantic similarity values between the target sample of text and each of the textual records are determined. Determining a particular semantic similarity value between the target sample of text and a particular textual record of the corpus includes: (i) determining individual semantic similarity values between the target sample of text and each of the segments of text indicated by the particular textual record, and (ii) generating the particular semantic similarity value between the target sample of text and the particular textual record based on the individual semantic similarity values. A textual record is then selected based on the semantic similarities.
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公开(公告)号：US10445661B2
公开(公告)日：2019-10-15
申请号：US15717796
申请日：2017-09-27
Applicant: ServiceNow, Inc.
Inventor： Nikhil Bendre , Fernando Ros , Kannan Govindarajan , Baskar Jayaraman , Aniruddha Thakur , Sriram Palapudi , Firat Karakusoglu
Abstract: A network system may include a plurality of trainer devices and a computing system disposed within a remote network management platform. The computing system may be configured to: receive, from a client device of a managed network, information indicating (i) training data that is to be used as basis for generating a machine learning (ML) model and (ii) a target variable to be predicted using the ML model; transmit an ML training request for reception by one of the plurality of trainer devices; provide the training data to a particular trainer device executing a particular ML trainer process that is serving the ML training request; receive, from the particular trainer device, the ML model that is generated based on the provided training data and according to the particular ML trainer process; predict the target variable using the ML model; and transmit, to the client device, information indicating the target variable.
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Patent Agency Ranking
公开(公告)号：US11836268B2
公开(公告)日：2023-12-05
申请号：US17062409
申请日：2020-10-02
Applicant: ServiceNow, Inc.
Inventor： Virendra Kumar Mehta , Sriram Palapudi
IPC: G06F21/62 , G06F21/60 , G06N20/00 , G06F8/658 , G06F18/214
CPC classification number: G06F21/6227 , G06F8/658 , G06F18/214 , G06F21/602 , G06N20/00
Abstract: A request to perform a prediction using a machine learning model of a specific entity is received. A specific security key for the machine learning model of the specific entity is received. At least a portion of the machine learning model is obtained from a multi-tenant machine learning model storage. The machine learning model is unlocked using the specific security key and the requested prediction is performed. A result of the prediction is provided from a prediction server.
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公开(公告)号：US20220108035A1
公开(公告)日：2022-04-07
申请号：US17062409
申请日：2020-10-02
Applicant: ServiceNow, Inc.
Inventor： Virendra Kumar Mehta , Sriram Palapudi
Abstract: A request to perform a prediction using a machine learning model of a specific entity is received. A specific security key for the machine learning model of the specific entity is received. At least a portion of the machine learning model is obtained from a multi-tenant machine learning model storage. The machine learning model is unlocked using the specific security key and the requested prediction is performed. A result of the prediction is provided from a prediction server.
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公开(公告)号：US20200351383A1
公开(公告)日：2020-11-05
申请号：US16402800
申请日：2019-05-03
Applicant: ServiceNow, Inc.
Inventor： Baskar Jayaraman , Aniruddha Madhusudhan Thakur , Kannan Govindarajan , Andrew Kai Chiu Wong , Sriram Palapudi
Abstract: A remote network management platform is provided that includes an end-user computational instance dedicated to a managed network, a training computational instance, and a prediction computational instance. The training instance is configured to receive a corpus of textual records from the end-user instance and to determine therefrom a machine learning (ML) model to determine the numerical similarity between input textual records and textual records in the corpus of textual records. The prediction instance is configured to receive the ML model and an additional textual record from the end-user instance, to use the ML model to determine respective numerical similarities between the additional textual record and the textual records in the corpus of textual records, and to transmit, based on the respective numerical similarities, representations of one or more of the textual records in the corpus of textual records to the end-user computational instance.
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公开(公告)号：US12299397B2
公开(公告)日：2025-05-13
申请号：US17448667
申请日：2021-09-23
Applicant: ServiceNow, Inc.
Inventor： Omer Anil Turkkan , Firat Karakusoglu , Sriram Palapudi
IPC: G06F40/30 , G06F40/205 , G06F40/284
Abstract: Systems and methods are provided to compare a target sample of text to a set of textual records, each textual record including a sample of text and an indication of one or more segments of text within the sample of text. Semantic similarity values between the target sample of text and each of the textual records are determined. Determining a particular semantic similarity value between the target sample of text and a particular textual record of the corpus includes: (i) determining individual semantic similarity values between the target sample of text and each of the segments of text indicated by the particular textual record, and (ii) generating the particular semantic similarity value between the target sample of text and the particular textual record based on the individual semantic similarity values. A textual record is then selected based on the semantic similarities.
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公开(公告)号：US11595484B2
公开(公告)日：2023-02-28
申请号：US16402800
申请日：2019-05-03
Applicant: ServiceNow, Inc.
Inventor： Baskar Jayaraman , Aniruddha Madhusudhan Thakur , Kannan Govindarajan , Andrew Kai Chiu Wong , Sriram Palapudi
Abstract: A remote network management platform is provided that includes an end-user computational instance dedicated to a managed network, a training computational instance, and a prediction computational instance. The training instance is configured to receive a corpus of textual records from the end-user instance and to determine therefrom a machine learning (ML) model to determine the numerical similarity between input textual records and textual records in the corpus of textual records. The prediction instance is configured to receive the ML model and an additional textual record from the end-user instance, to use the ML model to determine respective numerical similarities between the additional textual record and the textual records in the corpus of textual records, and to transmit, based on the respective numerical similarities, representations of one or more of the textual records in the corpus of textual records to the end-user computational instance.
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