公开(公告)号：US20220229986A1

公开(公告)日：2022-07-21

申请号：US17579156

申请日：2022-01-19

Applicant: ServiceNow, Inc.

Inventor： Rammohan Narendula ,  Edwin Sapugay ,  Anil Kumar Madamala ,  Benjamin Nicklaus Greer ,  Swathi Kumar Chadalavada

IPC: G06F40/284 ,  G06F40/253 ,  G06F40/247 ,  G06F40/205 ,  G06F40/30

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. In particular, taxonomy lookup sources can be compiled from suitable taxonomy source data that represents relationships between various entities within a domain of a client. These taxonomy lookup sources can extract taxonomy segmentations from utterances, such as received user utterances and sample utterances of an intent-entity model. The taxonomy segmentations can then be leveraged by the NLU system to perform vocabulary injection to expand the number of meaning representations in the utterance meaning model and/or the understanding model, increasing the likelihood of matches being located during a meaning search operation. Additionally, the taxonomy lookup sources can be leveraged by the NLU system to enable validation of sample utterances submitted for inclusion in the intent-entity model.

公开(公告)号：US20210342547A1

公开(公告)日：2021-11-04

申请号：US17304918

申请日：2021-06-28

Applicant: ServiceNow, Inc.

Inventor： Edwin Sapugay ,  Anil Kumar Madamala ,  Maxim Naboka ,  Srinivas SatyaSai Sunkara ,  Lewis Savio Landry Santos ,  Murali B. Subbarao

IPC: G06F40/30 ,  G06F40/35 ,  G06F40/295

Abstract: An agent automation system includes a memory configured to store a reasoning agent/behavior engine (RA/BE) including a first persona and a current context and a processor configured to execute instructions of the RA/BE to cause the first persona to perform actions comprising: receiving intents/entities of a first user utterance; recognizing a context overlay cue in the intents/entities of the first user utterance, wherein the context overlay cue defines a time period; updating the current context of the RA/BE by overlaying context information from at least one stored episode associated with the time period; and performing at least one action based on the intents/entities of the first user utterance and the current context of the RA/BE.

公开(公告)号：US11087090B2

公开(公告)日：2021-08-10

申请号：US16239147

申请日：2019-01-03

Applicant: ServiceNow, Inc.

Inventor： Edwin Sapugay ,  Anil Kumar Madamala ,  Maxim Naboka ,  Srinivas SatyaSai Sunkara ,  Lewis Savio Landry Santos ,  Murali B. Subbarao

IPC: G06F40/30 ,  G06F40/35 ,  G10L15/22 ,  G06F40/295 ,  G10L15/26

Abstract: An agent automation system includes a memory configured to store a reasoning agent/behavior engine (RA/BE) including a first persona and a current context and a processor configured to execute instructions of the RA/BE to cause the first persona to perform actions comprising: receiving intents/entities of a first user utterance; recognizing a context overlay cue in the intents/entities of the first user utterance, wherein the context overlay cue defines a time period; updating the current context of the RA/BE by overlaying context information from at least one stored episode associated with the time period; and performing at least one action based on the intents/entities of the first user utterance and the current context of the RA/BE.

公开(公告)号：US10956683B2

公开(公告)日：2021-03-23

申请号：US16356815

申请日：2019-03-18

Applicant: ServiceNow, Inc.

Inventor： Edwin Sapugay ,  Anil Kumar Madamala ,  Maxim Naboka ,  Srinivas SatyaSai Sunkara ,  Lewis Savio Landry Santos ,  Murali B. Subbarao

IPC: G06F40/30 ,  G06N20/00 ,  G10L15/19 ,  G10L15/22 ,  G06N5/02 ,  G06F40/205 ,  G06F40/211 ,  G10L15/18 ,  G10L15/16

Abstract: An agent automation system implements a virtual agent that is capable of learning new words, or new meanings for known words, based on exchanges between the virtual agent and a user in order to customize the vocabulary of the virtual agent to the needs of the user or users. The agent automation framework has access to a corpus of previous exchanges between the virtual agent and the user, such as one or more chat logs. New words and/or new meanings for known words are identified within the corpus and new word vectors are generated for these new words and/or new meanings for known words and added to refine a word vector distribution model. The refined word vector distribution model is then utilized by the agent automation system to interact with the user.

公开(公告)号：US20210004443A1

公开(公告)日：2021-01-07

申请号：US16584499

申请日：2019-09-26

Applicant: ServiceNow, Inc.

Inventor： Edwin Sapugay ,  Maxim Naboka ,  Anil Madamala

IPC: G06F17/27 ,  G06F16/2455

Abstract: Present embodiments include an agent automation framework having an artifact pinning subsystem that pins meaning representations of a search space to enable the agent automation system to target particularly relevant candidates for improved inferences. To generate the search space, the artifact pinning subsystem may determine multiple understandings of sample utterances within intent-entity models to generate meaning representations. The sample utterances generally each belong to an identified intent that may have been labeled with a particular entity, within a structure defined by the intent-entity models. To validate the relevance of each meaning representation for an identified intent, the artifact pinning subsystem may pin meaning representations that include the particular intent and include a respective entity corresponding to the labeled entity. In addition to model-based entity pinning, the search space may also be generated with respect to a contextual intent of an on-going conversation between a user and a behavior engine.

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.

公开(公告)号：US20220245361A1

公开(公告)日：2022-08-04

申请号：US17579260

申请日：2022-01-19

Applicant: ServiceNow, Inc.

Inventor： Rammohan Narendula ,  Edwin Sapugay ,  Maxim Naboka ,  Swathi Kumar Chadalavada

IPC: G06F40/35 ,  G06F40/295 ,  G06F40/284 ,  G06F40/186 ,  H04L51/02

Abstract: A natural language understanding (NLU) framework includes a lookup source framework that enables the lookup sources to be created and applied to understanding utterances. Each lookup source is associated with a respective lookup source template that defines the compile-time and inference-time behavior of the lookup source. For example, a lookup source template indicates which plugins are used by the lookup source, and may define property values that determine the operational behavior of each of these plugins during compile-time and/or inference-time operation of the lookup source. The lookup source framework includes a template manager that manages lookup source templates and determines a suitable lookup source template for each lookup source. The lookup source framework includes a lookup source template optimization subsystem that can apply a suitable optimization plugin to automatically determine attribute values to be included in an optimized lookup source template of a lookup source of the lookup source system.

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.

公开(公告)号：US10970487B2

公开(公告)日：2021-04-06

申请号：US16239218

申请日：2019-01-03

Applicant: ServiceNow, Inc.

Inventor： Edwin Sapugay ,  Anil Kumar Madamala ,  Maxim Naboka ,  Srinivas SatyaSai Sunkara ,  Lewis Savio Landry Santos ,  Murali B. Subbarao

IPC: G06F40/30 ,  G06N20/00 ,  G10L15/19 ,  G10L15/22 ,  G06N5/02 ,  G06F40/205 ,  G06F40/211 ,  G10L15/18 ,  G10L15/16

Abstract: An agent automation system includes a memory configured to store a natural language understanding (NLU) framework and a model, wherein the model includes at least one original meaning representation. The system includes a processor configured to execute instructions of the NLU framework to cause the agent automation system to perform actions including: performing rule-based generalization of the model to generate at least one generalized meaning representation of the model from the at least one original meaning representation of the model; performing rule-based refinement of the model to prune or modify the at least one generalized meaning representation of the model, or the at least one original meaning representation of the model, or a combination thereof; and after performing the rule-based generalization and the rule-based refinement of the model, using the model to extract intents/entities from a received user utterance.

公开(公告)号：US10740566B2

公开(公告)日：2020-08-11

申请号：US16179681

申请日：2018-11-02

Applicant: ServiceNow, Inc.

Inventor： Edwin Sapugay ,  Anil Kumar Madamala ,  Maxim Naboka ,  Srinivas SatyaSai Sunkara ,  Lewis Savio Landry Santos ,  Murali B. Subbarao

IPC: G06F40/30 ,  G06F16/28 ,  G06F16/2458 ,  G06N5/04 ,  G06F40/247 ,  G06F40/295 ,  G06N20/00

Abstract: An agent automation system includes a memory configured to store a corpus of utterances and a semantic mining framework and a processor configured to execute instructions of the semantic mining framework to cause the agent automation system to perform actions, wherein the actions include: detecting intents within the corpus of utterances; producing intent vectors for the intents within the corpus; calculating distances between the intent vectors; generating meaning clusters of intent vectors based on the distances; detecting stable ranges of cluster radius values for the meaning clusters; and generating an intent/entity model from the meaning clusters and the stable ranges of cluster radius values, wherein the agent automation system is configured to use the intent/entity model to classify intents in received natural language requests.