Methods and apparatus for real-time business visibility using persistent schema-less data storage

• US 20050228805A1
• Filed: 01/04/2005
• Published: 10/13/2005
• Est. Priority Date: 05/15/2001
• Status: Active Grant

• Current Assignee: Objectstore Incorporated
• Original Assignee: Metatomix, Inc. (ESW Capital, LLC)
• Inventors: Angelo, Robert F., Azmi, Amir, Kumar, Ashok, Britton, Colin P., Kaufman, Noah W., Bajpai, Chandra, Bigwood, David
• Granted Patent: US 7,640,239 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: Y10S 707/956 Hierarchical
• CPC Class Codes: Y10S 707/99932 Access augmentation or optimizing
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

The invention provides methods for enterprise business visibility that transform any of marketing, e-commerce and transactional from a plurality of legacy and other databases into resource description framework (RDF) syntax. This information can be time-stamped (e.g., with expiration dates) and stored in a central data store. Answers to queries are discerned by applying genetic algorithm-based search techniques to the holographic store, with the confidence levels of those answers is based in part, for example, on the time-stamps of the triples.

Claims

1. A digital data processing method comprising

transforming data from a plurality of databases into resource description framework (RDF) triples,

storing the triples in a data store, and

traversing one or more of the triples in the data store using a genetic algorithms in order to identify data responsive to a query.

2. A method according to claim 1, wherein the transforming step includes transforming data from a plurality of databases of disparate variety.

3. A method according to claim 2, wherein the data is any of marketing, e-commerce or transactional data.

4. A method according to claim 1, wherein the traversing step includes performing a plurality of searches on the data store, each search utilizing a different methodology.

5. A method according to claim 4, wherein the traversing step further comprises comparing results of one or more of the searches.

6. A method according to claim 5, wherein the traversing step further comprises discerning from the comparison one or more of the searches that produce better results and re-performing those one or more searches on the data store with any of additional terms or further granularity.

7. A method according to claim 1, wherein the storing step includes storing the triples such that related data from the plurality of databases is represented by uniform resource indicators (URIs) in a hierarchical ordering.

8. A method according to claim 7, wherein the RDF triples each have a subject, predicate and object and wherein the storing step includes storing the triples such that through each triple'"'"'s object that triple'"'"'s predicate and subject are referenced.

9. A digital data processing method for real-time business visibility comprising

collecting any of marketing, e-commerce and transactional data from a plurality of databases, at least two of which are of disparate variety,

storing the collected data in a schema-less data store.

10. A digital data processing method according to claim 9, comprising

transforming the collected data into resource description framework triples before storing it to the data store.

11. A digital data processing method according to claim 9, wherein the collecting step includes

applying one or more queries to the plurality of databases in order to collect the marketing, e-commerce and transactional data.

12. A digital data processing method according to claim 11, wherein the collecting step includes

applying the one or more queries in accord with a data mining technique.

13. A digital data processing method according to claim 11, comprising

traversing one or more of the RDF triples in the data store using a genetic algorithms in order to identify data responsive to a query.

14. A method according to claim 13, wherein the traversing step includes performing a plurality of searches on the data store, each search utilizing a different methodology.

15. A method according to claim 14, wherein the traversing step further comprises comparing results of one or more of the searches.

16. A method according to claim 15, wherein the traversing step further comprises discerning from the comparison one or more of the searches that produce better results and re-performing those one or more searches on the data store with any of additional terms or further granularity.

17. A digital data processing method comprising

transforming any of marketing, e-commerce and transactional data from a plurality of databases into resource description framework (RDF) triples, where at least two of the databases are of disparate variety,

storing the triples in a data store, and

forming collections from triples in the data store.

18. A digital data processing method according to claim 17, wherein

the storing step includes storing the triples such that related data from the plurality of databases are related in a hierarchy,

the forming step includes comparing sequential levels of triples in the hierarchy.

19. A digital data processing method according to claim 17, comprising

utilizing the forming step to form collections responsive to a query.

20. A digital data processing method according to claim 17, comprising

utilizing the forming step to reduce data redundancy.

21. A digital data processing method according to claim 17, wherein the storing step includes

storing any of version numbers, uniqueness identifiers, serial numbers, confidence level, or other adjectival data along with at least selected triples.

22. A digital data processing method comprising

transforming any of marketing, e-commerce and transactional data from a plurality of databases into resource description framework (RDF) triples, where at least two of the databases are of disparate variety,

storing the triples in a data store, and

storing expiry data with at least selected ones of the triples.

23. A digital data processing method according to claim 22, comprising any of deleting and tagging as stale triples based on expiry data associated therewith.

24. A digital data processing method according to claim 22, comprising

searching the triples for data responsive to a query,

returning such data along with a confidence factor.

25. A digital data processing method according to claim 24, comprising

generating the confidence factor based on expiry data associated with a triple.