17947369. AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES simplified abstract (Dell Products L.P.)
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 17947369 titled 'AUTOMATICALLY PREDICTING DISPATCH-RELATED DATA USING MACHINE LEARNING TECHNIQUES
Simplified Explanation
The patent application describes methods, apparatus, and processor-readable storage media for automatically predicting dispatch-related data using machine learning techniques.
- Obtaining data from user channels related to an issue
- Determining that a dispatch is needed to resolve the issue
- Predicting approval mode and outcome of the dispatch using machine learning
- 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 processes and improve efficiency.
Problems Solved
This technology helps in predicting dispatch-related data accurately, reducing manual intervention, and streamlining operations in various industries.
Benefits
The benefits of this technology include improved decision-making, faster response times, cost savings, and enhanced customer satisfaction.
Potential Commercial Applications
Optimizing dispatch processes in transportation companies, improving emergency response systems, and enhancing customer service operations in various industries.
Possible Prior Art
One possible prior art could be the use of predictive analytics in dispatch management systems to optimize resource allocation and improve response times.
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 technology for dispatch predictions.
What types of machine learning techniques are specifically used in this technology?
The article does not specify the exact machine learning algorithms or techniques employed in predicting dispatch-related data.
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.
