Dell products l.p. (20240095751). AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES simplified abstract
Contents
- 1 AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES
Organization Name
Inventor(s)
Divya Maddi of Round Rock TX (US)
Hung T. Dinh of Austin TX (US)
Bijan Kumar Mohanty of Austin TX (US)
AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240095751 titled 'AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES
Simplified Explanation
The abstract describes methods, apparatus, and processor-readable storage media for automatically predicting dispatch-related data using machine learning techniques. The process involves obtaining data related to an issue, determining the need for a dispatch, predicting approval mode and outcome of the dispatch using machine learning, and taking automated actions based on the predictions.
- Obtaining data from user channels related to an issue
- Determining the need for a dispatch to resolve the issue
- Predicting approval mode and outcome of the dispatch using machine learning techniques
- Performing automated actions based on the predicted approval mode and outcome
Potential Applications
This technology could be applied in customer service centers, emergency response systems, and logistics companies to optimize dispatch operations and improve efficiency.
Problems Solved
This technology helps in automating the dispatch process, reducing manual intervention, and improving decision-making based on predictive analytics.
Benefits
The benefits of this technology include faster response times, better resource allocation, cost savings, and improved customer satisfaction.
Potential Commercial Applications
"Predictive Dispatch Automation in Customer Service Centers"
Possible Prior Art
One possible prior art could be the use of predictive analytics in logistics and supply chain management to optimize routing and scheduling of deliveries.
Unanswered Questions
How does this technology handle real-time data processing for dispatch predictions?
This article does not provide details on the real-time processing capabilities of the system and how it ensures timely dispatch decisions based on the latest data.
What are the potential limitations or challenges faced in implementing this technology in different industries?
The article does not address the potential challenges or limitations that may arise when implementing this technology in various industries, such as data privacy concerns, integration with existing systems, or scalability issues.
Original Abstract Submitted
methods, apparatus, and processor-readable storage media for automatically predicting dispatch-related data using machine learning techniques are provided herein. an example computer-implemented method includes obtaining data, from one or more user channels, pertaining to at least one issue; determining, based at least in part on the obtained data, that at least one dispatch is to be carried out in connection with attempting to resolve the at least one issue; predicting, by processing at least a portion of the obtained data using one or more machine learning techniques, an approval mode associated with the at least one dispatch and at least one outcome associated with the at least one dispatch; and performing one or more automated actions based at least in part on one or more of the predicted approval mode and the at least one predicted outcome.
