17931118. ENHANCING DIALOGUE MANAGEMENT SYSTEMS USING FACT FETCHERS simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

ENHANCING DIALOGUE MANAGEMENT SYSTEMS USING FACT FETCHERS

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Harold Hannon of Lewisville TX (US)

Daniel M. Yellin of Raanana (IL)

ENHANCING DIALOGUE MANAGEMENT SYSTEMS USING FACT FETCHERS - A simplified explanation of the abstract

This abstract first appeared for US patent application 17931118 titled 'ENHANCING DIALOGUE MANAGEMENT SYSTEMS USING FACT FETCHERS

Simplified Explanation

The embodiment described in the abstract enhances dialogue management systems by enriching contextual data using fact fetchers.

• Automatically intercept a received query sent to a dialogue management system.
• Automatically tag language in the received query using a trained classifier.
• Identify applicable associated fact fetchers.
• Utilize the associated fact fetcher to identify additional contextual data.
• Generate an updated dialogue including the additional contextual data.
• Run a trained language model on the updated dialogue to generate a response for the received query.

Potential Applications

This technology could be applied in customer service chatbots, virtual assistants, and automated help desks to provide more accurate and relevant responses to user queries.

Problems Solved

This technology solves the problem of limited contextual understanding in dialogue management systems, leading to more effective and personalized interactions with users.

Benefits

The benefits of this technology include improved user experience, increased efficiency in handling queries, and enhanced accuracy in responses provided by dialogue management systems.

Potential Commercial Applications

Optimizing Customer Interactions with Enhanced Dialogue Management Systems

Original Abstract Submitted

An embodiment for enhancing dialogue management systems by enriching contextual data using fact fetchers. The embodiment may automatically intercept a received query sent to a dialogue management system. The embodiment may automatically tag language in the received query using a trained classifier and identify applicable associated fact fetchers. The embodiment may automatically utilize the associated fact fetcher to identify additional contextual data. The embodiment may automatically generate an updated dialogue including the additional contextual data. The embodiment may automatically run a trained language model on the updated dialogue to generate a response for the received query.