AI-Based Cloud Configurator Using User Utterences

Patent metadata

Field	Value
Publication number	US-2022239567-A1
Application number	US-202117156865-A
Country	US
Kind code	A1
Filing date	Jan 25, 2021
Priority date	Jan 25, 2021
Publication date	Jul 28, 2022
Grant date	—

Abstract

Embodiments configure a cloud system that includes a plurality of cloud services. Embodiments receive a user utterance that includes a natural language and extract at least a first entity from the utterance. Embodiments translate the first entity into a cloud intent definition language entity and receive user feedback in response to presenting the cloud intent definition language entity. Embodiments generate an intent based on the cloud intent definition language entity and the feedback and compile the intent into a cloud services policy to be deployed by the cloud system.

First claim

What is claimed is:

1 . A method of configuring a cloud system comprising a plurality of cloud services, the method comprising:
receiving a user utterance comprising a natural language; extracting at least a first entity from the utterance; translating the first entity into a cloud intent definition language entity; receive user feedback in response to presenting the cloud intent definition language entity; generating an intent based on the cloud intent definition language entity and the feedback; and compiling the intent into a cloud services policy to be deployed by the cloud system.

2 . The method of claim 1 , wherein the extracting the first entity from the utterance comprises using a chatbot.

3 . The method of claim 1 , wherein the translating the first entity into the cloud intent definition language entity comprises using a trained neural network.

4 . The method of claim 3 , wherein the trained neural network comprises a neural sequence-to-sequence learning model comprising a plurality of Recurrent Neural Network with Long Short-Term Memory hidden units.

5 . The method of claim 1 , wherein the cloud intent definition language entity comprises an intent definition language that provides an abstraction layer between the cloud services policy and the natural language.

6 . The method of claim 3 , further comprising replacing the first entity with a token using anonymization.

7 . The method of claim 1 , wherein the cloud services policy comprises at least one of policies related to: computing, network, security, analytics, or logging and monitoring.

8 . A cloud configurator system comprising:
an entities extractor adapted to receive a user utterance comprising a natural language and extract at least a first entity from the utterance; an intent translator adapted to translate the first entity into a cloud intent definition language entity; and an intent deployer adapted to receive user feedback in response to presenting the cloud intent definition language entity, generate an intent based on the cloud intent definition language entity and the feedback and compile the intent into a cloud services policy to be deployed by a cloud system.

9 . The system of claim 8 , the entities extractor comprising using a chatbot.

10 . The system of claim 8 , the intent translator comprising a trained neural network.

11 . The system of claim 10 , wherein the trained neural network comprises a neural sequence-to-sequence learning model comprising a plurality of Recurrent Neural Network with Long Short-Term Memory hidden units.

12 . The system of claim 8 , wherein the cloud intent definition language entity comprises an intent definition language that provides an abstraction layer between the cloud services policy and the natural language.

13 . The system of claim 10 , the intent translator further adapted to replace the first entity with a token using anonymization.

14 . The system of claim 8 , wherein the cloud services policy comprises at least one of policies related to: computing, network, security, analytics, or logging and monitoring.

15 . A computer-readable medium having instructions stored thereon that, when executed by one or more processors, cause the processors to configure a cloud system comprising a plurality of cloud services, the configuring comprising:
receiving a user utterance comprising a natural language; extracting at least a first entity from the utterance; translating the first entity into a cloud intent definition language entity; receive user feedback in response to presenting the cloud intent definition language entity; generating an intent based on the cloud intent definition language entity and the feedback; and compiling the intent into a cloud services policy to be deployed by the cloud system.

16 . The computer-readable medium of claim 15 , wherein the extracting the first entity from the utterance comprises using a chatbot.

17 . The computer-readable medium of claim 15 , wherein the translating the first entity into the cloud intent definition language entity comprises using a trained neural network.

18 . The computer-readable medium of claim 17 , wherein the trained neural network comprises a neural sequence-to-sequence learning model comprising a plurality of Recurrent Neural Network with Long Short-Term Memory hidden units.

19 . The computer-readable medium of claim 15 , wherein the cloud intent definition language entity comprises an intent definition language that provides an abstraction layer between the cloud services policy and the natural language.

20 . The computer-readable medium of claim 15 , wherein the cloud services policy comprises at least one of policies related to: computing, network, security, analytics, or logging and monitoring.

Assignees

• Oracle Int Corp

Inventors

• Manuel-Devadoss Johnson

Classifications

• G06N3/044

  Recurrent networks, e.g. Hopfield networks · CPC title

• G06N3/045

  Combinations of networks · CPC title

• G06N3/09

  Supervised learning · CPC title

• G06N3/091

  Active learning · CPC title

• G06N3/0455

  Auto-encoder networks; Encoder-decoder networks · CPC title