International business machines corporation (20240127085). TARGETED DATA ACQUISITION FOR MODEL TRAINING simplified abstract
Contents
- 1 TARGETED DATA ACQUISITION FOR MODEL TRAINING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 TARGETED DATA ACQUISITION FOR MODEL TRAINING - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
TARGETED DATA ACQUISITION FOR MODEL TRAINING
Organization Name
international business machines corporation
Inventor(s)
Ritesh Kumar Gupta of Hyderabad (IN)
Vijay Ekambaram of Chennai (IN)
Smitkumar Narotambhai Marvaniya of Bangalore (IN)
TARGETED DATA ACQUISITION FOR MODEL TRAINING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240127085 titled 'TARGETED DATA ACQUISITION FOR MODEL TRAINING
Simplified Explanation
The abstract of the patent application describes a method for targeted acquisition of data for model training by identifying attributes of classified samples and generating tailored queries to retrieve additional training data for a classification model.
- The method involves identifying attributes of classified samples in a collection.
- Tailored queries are generated based on the identified attributes to retrieve more training data.
- The goal is to train the classification model more accurately and avoid incorrect sample classification.
Potential Applications
This technology could be applied in various fields such as:
- Machine learning
- Data analysis
- Pattern recognition
Problems Solved
This technology helps address the following issues:
- Inaccurate classification of samples
- Insufficient training data for model training
Benefits
The benefits of this technology include:
- Improved accuracy in classification
- Enhanced model training
- Avoidance of misclassification errors
Potential Commercial Applications
Potential commercial applications of this technology could include:
- Data mining software
- Predictive analytics tools
- Fraud detection systems
Possible Prior Art
One possible prior art for this technology could be:
- Similar methods used in machine learning research
Unanswered Questions
1. How does the method determine which attributes are most relevant for generating tailored queries? 2. Are there any limitations to the size or type of data that can be retrieved using this method?
Original Abstract Submitted
targeted acquisition of data for model training includes identifying attributes of classified samples of a collection of samples classified by a classification model, and generating at least one query based on the identified attributes, the at least one query tailored, based on the attributes, to retrieve additional training data for training the classification model to more accurately classify samples and avoid incorrect sample classification.
