International business machines corporation (20240112074). NATURAL LANGUAGE QUERY PROCESSING BASED ON MACHINE LEARNING TO PERFORM A TASK simplified abstract

NATURAL LANGUAGE QUERY PROCESSING BASED ON MACHINE LEARNING TO PERFORM A TASK

Organization Name

international business machines corporation

Inventor(s)

Bryson Chisholm of Stevensville (CA)

Shikhar Kwatra of San Jose CA (US)

Shaikh Shahriar Quader of Oshawa (CA)

Ayesha Bhangu of Whitby (CA)

Jack Zhang of Unionville (CA)

Shabana Dhayananth of Brampton (CA)

Tarandeep kaur Randhawa of Stratford (CA)

NATURAL LANGUAGE QUERY PROCESSING BASED ON MACHINE LEARNING TO PERFORM A TASK - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240112074 titled 'NATURAL LANGUAGE QUERY PROCESSING BASED ON MACHINE LEARNING TO PERFORM A TASK

Simplified Explanation

The present invention involves a method for processing natural language queries to perform tasks using machine learning models and data retrieval from multiple sources.

• Machine learning model determines task from natural language query
• Query generated to retrieve data from different sources
• Data for task retrieved from multiple sources
• Task performed using retrieved data

Potential Applications

This technology can be applied in various fields such as customer service, data analysis, and information retrieval systems.

Problems Solved

This technology streamlines the process of task performance based on natural language queries, reducing manual effort and improving efficiency.

Benefits

The benefits of this technology include faster task completion, improved accuracy in task performance, and enhanced user experience with natural language interfaces.

Potential Commercial Applications

Potential commercial applications of this technology include chatbots, virtual assistants, and search engines that can understand and execute tasks based on natural language queries.

Possible Prior Art

One possible prior art for this technology could be existing natural language processing systems that perform tasks based on user queries.

How does this technology handle ambiguous natural language queries?

This technology uses machine learning models to determine the most likely task based on the context of the query and available data sources.

What measures are in place to ensure data security and privacy when retrieving data from multiple sources?

Data security protocols and encryption methods are implemented to protect sensitive information when retrieving data from different sources.

Original Abstract Submitted

an embodiment of the present invention extracts information from a natural language query requesting performance of a task. a machine learning model determines a task that corresponds to the task requested by the natural language query based on the extracted information. a query is generated for retrieving data from a plurality of different data sources based on the extracted information. the data for the determined task is retrieved from the plurality of different data sources based on the generated query. the determined task is performed using the retrieved data. present invention embodiments include a method, system, and computer program product for processing a natural language query in substantially the same manner described above.