18073314. DEEP MINING OF ENTERPRISE DATA SOURCES simplified abstract (SAP SE)
Contents
DEEP MINING OF ENTERPRISE DATA SOURCES
Organization Name
Inventor(s)
James Michael Amulu of Chennai (IN)
Ranganathan Natarajan of Bangalore (IN)
DEEP MINING OF ENTERPRISE DATA SOURCES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18073314 titled 'DEEP MINING OF ENTERPRISE DATA SOURCES
The patent application describes methods and apparatus for deep mining of data sources, providing extended reach into structured databases and unstructured data sources. Direct evaluation of columns for relevance to a client query is emphasized, offering a wider array of potentially relevant columns compared to conventional tools.
- Direct column evaluation is extended to unstructured data sources.
- A broad interface allows seamless search across structured and unstructured data sources.
- Superior results are achieved with reduced computing resource utilization.
- Limitations of human expertise are overcome.
- Efficiencies are enhanced through caching, ranking of columns or results, search refinement, and customized responses.
Potential Applications: This technology could be applied in data analytics, business intelligence, market research, and information retrieval systems.
Problems Solved: The technology addresses the limitations of conventional tools in evaluating data columns for relevance, providing a more comprehensive and efficient approach to data mining.
Benefits: The technology offers improved accuracy, efficiency, and scalability in data mining operations, leading to better decision-making and insights for users.
Commercial Applications: This technology could be utilized in industries such as finance, healthcare, e-commerce, and research institutions for data analysis and knowledge discovery purposes.
Prior Art: Researchers and practitioners in the field of data mining, information retrieval, and database management may find relevant prior art in similar techniques and approaches to deep mining of data sources.
Frequently Updated Research: Stay informed about the latest advancements in data mining, artificial intelligence, and machine learning to enhance the capabilities of this technology.
Questions about Deep Data Mining: 1. How does deep mining of data sources differ from traditional data mining techniques? 2. What are the key advantages of direct column evaluation in data mining operations?
Original Abstract Submitted
Methods and apparatus are disclosed for deep mining of data sources. A deep miner provides extended reach into available structured databases and/or unstructured data sources. Direct evaluation of columns for relevance to a client query provides a wider array of columns having potential relevance, compared to conventional tools relying on table evaluation. Direct column evaluation is extended to unstructured data sources. A broad interface extends the reach of search seamlessly across a wide range of structured and unstructured data sources. Disclosed techniques provide superior results with reduced computing resource utilization. Limitations of human expertise are overcome. Further efficiencies are achieved through caching, ranking of columns or results, search refinement, and customized responses.
