US 12,353,372 B2
Methods and systems for data management, integration, and interoperability
Srinivas Munuri, Iselin, NJ (US); Rutherford Le Blang, Iselin, NJ (US); and Girish J. Showkatramani, Iselin, NJ (US)
Assigned to Trigyan Corporation Inc., Iselin, NJ (US)
Filed by Trigyan Corporation Inc., Iselin, NJ (US)
Filed on Apr. 27, 2023, as Appl. No. 18/140,327.
Application 18/140,327 is a continuation in part of application No. 17/503,605, filed on Oct. 18, 2021, abandoned.
Prior Publication US 2023/0350862 A1, Nov. 2, 2023
Int. Cl. G06F 16/215 (2019.01); G06F 16/22 (2019.01); G06F 16/23 (2019.01); G06F 16/25 (2019.01); G06F 16/28 (2019.01)
CPC G06F 16/215 (2019.01) [G06F 16/2228 (2019.01); G06F 16/2365 (2019.01); G06F 16/258 (2019.01); G06F 16/285 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for data management, integration, and interoperability, the method comprising:
defining, by a data integration engine, at least one data model and asset by including data models, vocabulary, data quality rules, data mapping rules for at least one of, a particular data industry, a data domain, or a data subject area;
importing, by the data integration engine, data from a plurality of data sources;
performing, by the data integration engine, de-duplication of the imported data;
performing, by the data integration engine, data profiling of the imported data;
creating, by the data integration engine, linked data by semantic mapping, wherein creating the linked data by semantic mapping includes:
learning to perform an annotation task using features extracted from at least one column statistics feature of a relational table;
compressing at least one other feature into a fixed-size embedding using a subnetwork; and
training a two-fully connected layer network on at least one embedding feature and at least one column statistics feature for predicting a column type annotation for dataset.