View source for 17849444. MULTI-MODEL ENRICHMENT MEMORY AND CATALOG FOR BETTER SEARCH RECALL WITH GRANULAR PROVENANCE AND LINEAGE simplified abstract (Microsoft Technology Licensing, LLC)

=MULTI-MODEL ENRICHMENT MEMORY AND CATALOG FOR BETTER SEARCH RECALL WITH GRANULAR PROVENANCE AND LINEAGE=


==Organization Name==

[[:Category:Microsoft Technology Licensing, LLC|Microsoft Technology Licensing, LLC]]


[[Category:Microsoft Technology Licensing, LLC]]

==Inventor(s)==

[[:Category:Kevin Corley Wonus of Haymarket VA (US)|Kevin Corley Wonus of Haymarket VA (US)]][[Category:Kevin Corley Wonus of Haymarket VA (US)]]

[[:Category:Chelsea Ann Villanueva of Woodinville WA (US)|Chelsea Ann Villanueva of Woodinville WA (US)]][[Category:Chelsea Ann Villanueva of Woodinville WA (US)]]

[[:Category:Samuel Robert Lester of Issaquah WA (US)|Samuel Robert Lester of Issaquah WA (US)]][[Category:Samuel Robert Lester of Issaquah WA (US)]]

==MULTI-MODEL ENRICHMENT MEMORY AND CATALOG FOR BETTER SEARCH RECALL WITH GRANULAR PROVENANCE AND LINEAGE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17849444 titled 'MULTI-MODEL ENRICHMENT MEMORY AND CATALOG FOR BETTER SEARCH RECALL WITH GRANULAR PROVENANCE AND LINEAGE

==Simplified Explanation==

The patent application describes a multi-model data store that includes an enrichment catalog and an enrichment memory graph. Here are the key points:

* The data store takes raw data from a source raw datastore and enriches it using an enrichment function.
* The enriched data is stored in graph nodes, with edge associations indicating the type of enrichment and the confidence level.
* The enriched data is also stored in the enrichment catalog, along with breadcrumb provenance and lineage information that identifies the enrichment steps.
* Users can add additional enriched values and associations to the graph.
* Queries to the multi-model database start in the graph and then move to the enrichment catalog.
* Query results include the complete chain of enrichments from the source raw data records and fields.
* The system can generate virtual enrichment catalog records that link search values not found in the catalog to existing records via the graph.

Potential applications of this technology:

* Data enrichment and analysis in various industries such as finance, healthcare, and e-commerce.
* Building recommendation systems based on enriched data.
* Fraud detection and prevention by analyzing enriched data.

Problems solved by this technology:

* Efficiently storing and querying enriched data.
* Providing a comprehensive view of the enrichment process and lineage.
* Allowing users to easily add additional enriched values and associations.

Benefits of this technology:

* Improved data analysis and decision-making through enriched data.
* Enhanced data provenance and lineage tracking.
* Flexibility to add and query additional enriched values.


==Original Abstract Submitted==

A multi-model data store comprises an enrichment catalog and an enrichment memory graph. Raw data from a source raw datastore is enriched based on an enrichment function. Enriched data is stored in graph nodes with edge associations indicating the enrichment type and confidence level. The enriched data is also stored in the enrichment catalog with full breadcrumb provenance and lineage identifying, with cataloged enrichment steps, down to a record and field in the source raw datastore. Additional enriched values and associations between graph nodes can be entered in the graph by a user. Queries to the multi-model database begin in the graph and continue to the enrichment catalog. Query results include the full sequential chain of enrichments to source raw data records and fields, and may include dynamically generated virtual enrichment catalog records that link search values not found in the enrichment catalog to enrichment catalog records via the graph.



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