Systems and methods for generating context summaries for data transfers

Patent metadata

Field	Value
Publication number	US-2025328571-A1
Application number	US-202418640212-A
Country	US
Kind code	A1
Filing date	Apr 19, 2024
Priority date	Apr 19, 2024
Publication date	Oct 23, 2025
Grant date	—

Abstract

The present disclosure relates to systems and methods for generating summaries about context of data transfers using trained machined learning models. There is provided a computer system, comprising a processor, a communications module coupled to the processor, and a memory coupled to the processor. The memory stores instructions that, when executed, configure the processor to receive an indication to view a record of a data transfer on a device, collect metadata associated with the data transfer and device data associated with the data transfer from the device, generate a context summary of the data transfer based on the metadata and the device data using a trained machine learning model, and transmit a signal to the device to display the context summary in association with the record of the data transfer.

First claim

What is claimed is:

1 . A computer system, comprising:
a processor; a communications module coupled to the processor; and a memory coupled to the processor, the memory storing instructions that, when executed, configure the processor to:
receive an indication to view a record of a data transfer on a device;
collect metadata associated with the data transfer and device data associated with the data transfer from the device;
generate a context summary of the data transfer based on the metadata and the device data using a trained machine learning model; and
transmit a signal to the device to display the context summary in association with the record of the data transfer.

2 . The system of claim 1 , wherein the metadata comprises one or more of a date and a time of the data transfer.

3 . The system of claim 2 , wherein the device data comprises one or more of location data, calendar data, image data, contact data, and email data of or on the device.

4 . The system of claim 3 , wherein one or more of the location data, the image data, and the email data are identified to be associated with the data transfer when a date and timestamp associated respectively with the location data, the image data, and the email data are within a predetermined threshold relative to the date and the time of the data transfer.

5 . The system of claim 3 , wherein the image data comprises an image, the trained machine learning model comprises an image processing neural network trained to analyze and describe the image, and the instructions, when executed, further configure the processor to collect the image data by generating a description of the image using the image processing neural network.

6 . The system of claim 4 , wherein the instructions, when executed, further configure the processor to obtain supplementary data based on the metadata and the device data by processing the metadata and the device data.

7 . The system of claim 6 , wherein the instructions, when executed, further configure the processor to obtain the supplementary data by querying third-party databases using the metadata and the device data.

8 . The system of claim 7 , wherein the supplementary data comprises one or more of weather data and traffic data.

9 . The system of claim 6 , wherein the instructions, when executed, further configure the processor to generate the context summary by determining key points relating to context of the data transfer from the metadata, the device data, and the supplementary data using the trained machine learning model.

10 . The system of claim 9 , wherein the trained machine learning model is a text summarizer that uses natural language processing (NLP) techniques.

11 . The system of claim 10 , wherein the context summary is a listing of the key points.

12 . The system of claim 6 , wherein the trained machine learning model is a generative artificial intelligence (GenAI) model, and wherein the instructions, when executed, further configure the processor to:
generate a prompt to the GenAI model for generating the context summary, the prompt including the metadata, the device data, and the supplementary data; and obtain, from the GenAI model responsive to the prompt, the context summary, wherein the context summary is a natural language explanation of context of the data transfer.

13 . The system of claim 12 , wherein the GenAI model is a large language model (LLM).

14 . A method comprising:
receiving an indication to view a record of a data transfer on a device; identifying metadata associated with the data transfer and device data associated with the data transfer from the device; generating a context summary of the data transfer based on the metadata and the device data using a trained machine learning model; and displaying the context summary on the device in association with the record of the data transfer.

15 . The method of claim 14 , wherein the device data comprises one or more of location data, calendar data, image data, contact data, and email data of or on the device.

16 . The method of claim 15 , further comprising:
generating supplementary data based on the metadata and the device data by processing the metadata and the device data.

17 . The method of claim 16 , wherein generating the supplementary data comprises querying third-party databases with the metadata and the device data.

18 . The method of claim 16 , wherein generating the context summary comprises determining key points relating to context of the data transfer from the metadata, the device data, and the supplementary data using the trained machine learning model.

19 . The method of claim 16 , wherein the trained machine learning model is a generative artificial intelligence (GenAI) model, the method further comprising:
generating a prompt to the GenAI model for generating the context summary, the prompt including the metadata, the device data, and the supplementary data; and obtain, from the GenAI model responsive to the prompt, the context summary, wherein the context summary is a natural language explanation of context of the data transfer.

20 . A computer-readable medium comprising instructions stored therein which, when executed by a processor, cause a computer to:
receive an indication to view a record of a data transfer on a device; identify metadata and device data associated with the data transfer; generate a context summary of the data transfer based on the metadata and the device data using a trained machine learning model; and display the context summary on the device in association with the record of the data transfer.

Assignees

• Toronto Dominion Bank

Inventors

• Bajaj Hitesh
• Dunjic Milos
• Tax David Samuel
• Prendergast Jonathan Joseph
• Sharma Mohit
• Singha Hazari Abhijit
• Gupta Pranay
• Rastogi Kushank
• Kelly Thomas

Classifications

• G06F16/383

  using metadata automatically derived from the content · CPC title

• G06F16/345 Primary

  Summarisation for human users · CPC title