International Business Machines Corporation

Madhusmita P Patil

Ritesh Kumar Gupta

Bijo A Thomas

Swetha Patil

Ramesh Rajagopalan

Arundhathi Erla

Vijay Kumar Ananthapur Bache

Rengia Ramaiyan Vasudevan

Nagesh K Mantripragada

Gokul B Alex

Joyil Joseph

A system for cross-domain adaptation includes an analysis module, a set configuration module, a set multiplexer, a scalable bloom filter, a mapping module, and an aggregation module. The cross-domain adaptation system may allow for bloom filter adaptation across industries and domains with minimal increases in necessary hardware and consequentially minimal increases in power consumption and cost of area. A method for multi-domain adaptation in datasets includes performing multi-domain semantic analysis on a set of data, providing two complementary domain adaptive sets, processing the complementary domain adaptive sets to provide a multi-fractal representation of the dataset, processing the multi-fractal representation of the dataset with a scalable bloom filter to provide two filtered domain adaptive sets, providing a bijective holomorphic map of the filtered domain adaptive sets, and processing the bijective holomorphic map to provide multi-domain insight aggregator output. A computer program product corresponding to the method is also disclosed.

Cross-domain adaptation using bloom filters

A transformation method and system is provided. The method includes generating a data hub application configured to embed extract, transform, and load (ETL) processes. The data hub application is linked to source tables and target tables. Meta data associated with the source and target tables is transferred from virtual views of the data hub application to an ETL work area of the ETL processes. An ETL job is generated and linked to the data hub application. ETL processes are executed and results are determined.

Automated data analysis and transformation

Growing community of inventors

Hyderabad Telangana, India

Madhusmita P Patil