IP Library Patent Application 19248620
Patent Application
App. No. 19/248,620

APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR GENERATING AN AUTOMATED RESOLUTION ACTION USING A KNOWLEDGE BASE SYSTEM AND A TRAINED MACHINE LEARNING MODEL

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Quick Facts
Patent No.
US None
App. No.
19/248,620
Abstract

Methods, apparatuses, or computer program products provide for generating an automated resolution action using a knowledge base system and a trained machine learning model. In some examples, a service message object is received via a communication channel of a plurality of communication channels and the service message object defines a feature dataset associated with a service request for an application framework, a knowledge base system is queried based on the feature dataset, a knowledge base data structure is received from the knowledge base system in response to the query, the knowledge base data structure is input to a machine learning model trained for reading comprehension to generate a resolution data object associated with a service resolution for the service request, and a resolution action is initiated for the service request based on the resolution data object.

Claims (55)

1 . An apparatus comprising one or more processors and one or more storage devices storing instructions that are operable, when executed by the one or more processors, to cause the one or more processors to:

receive a service message object via a communication channel of a plurality of communication channels, wherein the service message object defines a feature dataset associated with a service request for an application framework;

query a knowledge base system based on the feature dataset;

receive a knowledge base data structure from the knowledge base system in response to the query;

input the knowledge base data structure to a machine learning model trained for reading comprehension to generate a resolution data object associated with a service resolution for the service request; and

initiate a resolution action for the service request based on the resolution data object.

2 . The apparatus of claim 1 , wherein the machine learning model is a Bidirectional Encoder Representations from Transformers (BERT) language model.

3 . The apparatus of claim 1 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:

transmit a resolution message object associated with the resolution data object to a user device via the communication channel.

4 . The apparatus of claim 1 , wherein the service message object comprises unstructured service message data, and wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:

transform the unstructured service message data into the feature dataset associated with the service request.

5 . The apparatus of claim 1 , wherein the knowledge base system comprises a searchable database associated with resolution information, and wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:

query the searchable database based on the feature dataset.

6 . The apparatus of claim 1 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:

modify one or more parameters of the machine learning model based on the service message object and the resolution action.

7 . The apparatus of claim 1 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:

input the service message object to a generative artificial intelligence model to generate resolution information for the service request; and

initiate the resolution action for the service request based on the resolution data object and the resolution information.

8 . The apparatus of claim 1 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more processors, to further cause the one or more processors to:

input the knowledge base data structure to a generative artificial intelligence model to generate resolution information for the service request; and

initiate the resolution action for the service request based on the resolution data object and the resolution information.

9 . The apparatus of claim 1 , wherein the communication channel corresponds to an email communication channel, a network portal interface communication channel, a user interface widget communication channel, a chat communication channel, or an application programming interface (API) communication channel.

10 . A computer-implemented method, comprising:

receiving a service message object via a communication channel of a plurality of communication channels, wherein the service message object defines a feature dataset associated with a service request for an application framework;

querying a knowledge base system based on the feature dataset;

receiving a knowledge base data structure from the knowledge base system in response to the query;

inputting the knowledge base data structure to a machine learning model trained for reading comprehension to generate a resolution data object associated with a service resolution for the service request; and

initiating a resolution action for the service request based on the resolution data object.

11 . The computer-implemented method of claim 10 , wherein the machine learning model is a Bidirectional Encoder Representations from Transformers (BERT) language model.

12 . The computer-implemented method of claim 10 , further comprising:

transmitting a resolution message object associated with the resolution data object to a user device via the communication channel.

13 . The computer-implemented method of claim 10 , wherein the service message object comprises unstructured service message data, and the computer-implemented method further comprising:

transforming the unstructured service message data into the feature dataset associated with the service request.

14 . The computer-implemented method of claim 10 , wherein the knowledge base system comprises a searchable database associated with resolution information, and the computer-implemented method further comprising:

querying the searchable database based on the feature dataset.

15 . The computer-implemented method of claim 10 , further comprising:

modifying one or more parameters of the machine learning model based on the service message object and the resolution action.

16 . The computer-implemented method of claim 10 , further comprising:

inputting the service message object to a generative artificial intelligence model to generate resolution information for the service request; and

initiating the resolution action for the service request based on the resolution data object and the resolution information.

17 . The computer-implemented method of claim 10 , further comprising:

inputting the knowledge base data structure to a generative artificial intelligence model to generate resolution information for the service request; and

initiating the resolution action for the service request based on the resolution data object and the resolution information.

18 . A computer program product, stored on a computer readable medium, comprising instructions that when executed by one or more computers cause the one or more computers to:

receive a service message object via a communication channel of a plurality of communication channels, wherein the service message object defines a feature dataset associated with a service request for an application framework;

query a knowledge base system based on the feature dataset;

receive a knowledge base data structure from the knowledge base system in response to the query;

input the knowledge base data structure to a machine learning model trained for reading comprehension to generate a resolution data object associated with a service resolution for the service request; and

initiate a resolution action for the service request based on the resolution data object.

19 . The computer program product of claim 18 , the computer program product further comprising instructions that when executed by the one or more computers cause the one or more computers to:

input the service message object to a generative artificial intelligence model to generate resolution information for the service request; and

initiate the resolution action for the service request based on the resolution data object and the resolution information.

20 . The computer program product of claim 18 , the computer program product further comprising instructions that when executed by the one or more computers cause the one or more computers to:

input the knowledge base data structure to a generative artificial intelligence model to generate resolution information for the service request; and

initiate the resolution action for the service request based on the resolution data object and the resolution information.

Assignments (4)
CORRECTIVE ASSIGNMENT TO CORRECT THE FIRST ASSIGNEES NAME PREVIOUSLY RECORDED ON REEL 71512 FRAME 470. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Jul 16, 2025
From: MANN, CHRISTOPHER
To: ATLASSIAN PTY LTD.; ATLASSIAN US, INC.
Reel/Frame 071979/0966 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 25, 2025
From: RUFLIN, MICHAEL; MANN, CHRISTOPHER; KUPPAN, OMPRAKASH; SHA, ZHOU
To: ATLASSIAN PTY LTD; ATLASSIAN (US) LLC
Reel/Frame 071512/0424 →
NUNC PRO TUNC ASSIGNMENT Recorded Jun 25, 2025
From: MANN, CHRISTOPHER
To: ATLASSIAN PTY LTD; ATLASSIAN US, INC.
Reel/Frame 071512/0470 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 25, 2025
From: ATLASSIAN (US) LLC
To: ATLASSIAN US, INC.
Reel/Frame 071512/0622 →