18097524. SYSTEM TO LABEL K-MEANS CLUSTERS WITH HUMAN UNDERSTANDABLE LABELS simplified abstract (Capital One Services, LLC)
SYSTEM TO LABEL K-MEANS CLUSTERS WITH HUMAN UNDERSTANDABLE LABELS
Organization Name
Inventor(s)
Reza Farivar of Champaign IL (US)
Austin Walters of Savoy IL (US)
Jeremy Goodsitt of Champaign IL (US)
Vincent Pham of Champaign IL (US)
Anh Truong of Champaign IL (US)
Galen Rafferty of Mahomet IL (US)
SYSTEM TO LABEL K-MEANS CLUSTERS WITH HUMAN UNDERSTANDABLE LABELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18097524 titled 'SYSTEM TO LABEL K-MEANS CLUSTERS WITH HUMAN UNDERSTANDABLE LABELS
Simplified Explanation
The patent application describes a system, method, and apparatus for generating labels for k-means clusters. The method involves accessing a database of data records and storing them in memory along with a cluster number for each record. The data records with the same cluster number form a cluster. The method then performs cluster-based analysis for each cluster with respect to a single feature to generate a single feature overlap score. The clusters are sorted, grouped, and labeled based on the predetermined number of features with the lowest overlap scores.
- The method involves accessing a database of data records and storing them in memory along with a cluster number for each record.
- Data records with the same cluster number form a cluster.
- Cluster-based analysis is performed for each cluster with respect to a single feature to generate a single feature overlap score.
- The clusters are sorted, grouped, and labeled based on the predetermined number of features with the lowest overlap scores.
Potential Applications
- Data clustering and categorization
- Data analysis and visualization
- Pattern recognition and classification
Problems Solved
- Efficient labeling and categorization of data clusters
- Simplifying the analysis of large datasets
- Improving data organization and understanding
Benefits
- Streamlined data analysis process
- Improved data organization and categorization
- Enhanced pattern recognition and classification capabilities
Original Abstract Submitted
Disclosed herein are system, method, and apparatus for generating labels for k-means clusters. The method includes accessing a plurality of data records from a database repository, and storing the plurality of data records into at least one of primary or secondary memory associated with at least one computer processor performing the method, along with a cluster number for each data record. All data records having a same cluster number form a cluster, and each record has been categorized or designated a cluster number out of a total K number of clusters. The method includes for each of a plurality of classification features, performing cluster-based analysis for a first cluster with respect to a single feature to generate a single feature overlap score. The method includes sorting, grouping, and generating a naming label for the first cluster based on the predetermined number of features having the lowest overlap scores.
