18101033. SELF-HEALING DATA CLUSTERS simplified abstract (American Express Travel Related Services Company, Inc.)

SELF-HEALING DATA CLUSTERS

Organization Name

American Express Travel Related Services Company, Inc.

Inventor(s)

Karina I. Alvarez Silverstein of Plantation FL (US)

Mahasweta Dhawan of New York NY (US)

Alan Wilson D'souza of New York NY (US)

Sayantan Dutta of Toronto (CA)

Anmol Handa of Gurugram (IN)

Shipali Jangra of New York NY (US)

Hen I. Kamil of Sunrise FL (US)

Rajendra Prasad Modadugu of Sunrise FL (US)

Sumit Prajapati of Sunrise FL (US)

Bhupesh Sharma of Gurugram (IN)

SELF-HEALING DATA CLUSTERS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18101033 titled 'SELF-HEALING DATA CLUSTERS

Simplified Explanation: The patent application describes a method for self-healing data clusters by evaluating candidates from a pool, generating unique pair combinations, identifying candidate data from existing records, assigning weights to matching rules, calculating distances between pairs, and clustering candidates into groups.

Key Features and Innovation:

• Method for self-healing data clusters
• Evaluation of candidates from a pool
• Generation of unique pair combinations
• Identification of candidate data from existing records
• Assignment of weights to matching rules
• Calculation of distances between pairs
• Clustering candidates into groups

Potential Applications: This technology can be applied in data management systems, database operations, and data linkage processes.

Problems Solved: This technology addresses the challenges of data clustering, data linkage, and data integrity in large datasets.

Benefits:

• Improved data accuracy
• Enhanced data clustering efficiency
• Automated data linkage processes
• Self-healing capabilities for data clusters

Commercial Applications: Potential commercial applications include data analytics platforms, cloud storage services, and data integration solutions in various industries.

Prior Art: Researchers can explore prior art related to data clustering algorithms, data linkage methods, and self-healing data systems.

Frequently Updated Research: Stay informed about advancements in data clustering algorithms, data linkage technologies, and self-healing data systems for continuous improvement in data management processes.

Questions about Self-Healing Data Clusters: 1. How does this technology improve data integrity in large datasets? 2. What are the key components of the self-healing process in data clusters?

Original Abstract Submitted

Disclosed are various embodiments for self-healing data clusters. One or more candidates are determined from the candidate pool to be evaluated with the new record. A unique pair combination is generated for each one of the candidates of the candidate pool and the new record. Next, candidate data for the one or more candidates is identified from the existing record based at least in part on one or more matching rules. A weight is assigned to one or more matching rules. Then, the candidate data of the one or more candidates and the new record is evaluated for a data linkage. A distance is calculated between each of the unique pair combinations. Finally, the candidates of the existing record and the new record are clustered into groups.