Abstract rule sets

• US 20070112827A1
• Filed: 11/10/2005
• Published: 05/17/2007
• Est. Priority Date: 11/10/2005
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Dettinger, Richard, Kolz, Daniel, Tenner, Jeffrey, Dietel, John
• Application Number:
  US11/272,583
• Publication Number:
  US 20070112827A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases

Abstract

A method, system and article of manufacture for processing rule sets and, more particularly, for processing abstract rule sets having one or more abstract rules. One embodiment provides a computer-implemented method of generating recommendations using a suitable rules engine. The method comprises retrieving an abstract rule having a conditional statement and a consequential statement. The consequential statement defines a particular recommendation that is returned when the conditional statement is satisfied. The conditional statement and the consequential statement are defined using logical field definitions defined in an abstraction model that models underlying physical data in a manner making a schema of the physical data transparent to a user of the abstraction model. The method further comprises transforming the abstract rule into a transformed rule; and executing, by the rules engine, the transformed rule. If the conditional statement is resolved to true for the executed transformed rule, the particular recommendation is returned.

Claims

1. A computer-implemented method of generating recommendations using a suitable rules engine, comprising:

retrieving an abstract rule having a conditional statement and a consequential statement;

wherein the consequential statement defines a particular recommendation that is returned when the conditional statement is satisfied;

wherein the conditional statement and the consequential statement are defined using logical field definitions defined in an abstraction model that models underlying physical data in a manner making a schema of the physical data transparent to a user of the abstraction model;

transforming the abstract rule into a transformed rule;

executing, by the rules engine, the transformed rule; and

if the conditional statement is resolved to true for the executed transformed rule, returning the particular recommendation.

2. The method of claim 1, wherein transforming the abstract rule comprises:

determining one or more inputs against which the conditional statement is resolved.

3. The method of claim 2, wherein determining the one or more inputs comprises:

selecting one or more field values from a query result set.

4. The method of claim 3, further comprising:

receiving user input selecting the abstract rule; and

displaying a query creation form to the user, the form being configured to guide the user through selection of suitable result fields for a query against a database, the suitable result fields requesting for the one or more field values.

5. The method of claim 4, wherein the suitable result fields correspond to fields included in the conditional statement and needed to resolve the conditional statement.

6. The method of claim 1, further comprising:

executing a query against a database;

receiving a result set for the executed query; and

determining, from the result set, one or more inputs against which the conditional statement is resolved;

wherein the transformed rule includes the inputs.

7. The method of claim 1, wherein retrieving the abstract rule is done in response to running an analysis routine referencing the abstract rule;

and wherein the returned particular recommendation is an analysis result for the analysis routine.

8. The method of claim 1, wherein transforming the abstract rule into the transformed rule comprises:

retrieving a specification of the abstract rule in a first computer-readable language; and

transforming the specification into a language which is accepted by the rules engine.

9. The method of claim 8, wherein the first computer-readable language is XML and/or the language which is accepted by the rules engine is ABLE Rule Language.

10. A computer-implemented method of creating an abstract rule, comprising:

creating a conditional statement using logical field definitions defined in an abstraction model that models underlying physical data in a manner making a schema of the physical data transparent to a user of the abstraction model;

creating, using the logical fields of the abstraction model, a consequential statement that defines a particular recommendation that is returned when the conditional statement is satisfied; and

associating the conditional statement with the consequential statement to generate the abstract rule.

11. A computer-readable medium containing a program which, when executed by a processor, performs operations for generating recommendations using a suitable rules engine, the operations comprising:

retrieving an abstract rule having a conditional statement and a consequential statement;

wherein the consequential statement defines a particular recommendation that is returned when the conditional statement is satisfied;

wherein the conditional statement and the consequential statement are defined using logical field definitions defined in an abstraction model that models underlying physical data in a manner making a schema of the physical data transparent to a user of the abstraction model;

transforming the abstract rule into a transformed rule;

executing, by the rules engine, the transformed rule; and

if the conditional statement is resolved to true for the executed transformed rule, returning the particular recommendation.

12. The computer-readable medium of claim 11, wherein transforming the abstract rule comprises:

determining one or more inputs against which the conditional statement is resolved.

13. The computer-readable medium of claim 12, wherein determining the one or more inputs comprises:

selecting one or more field values from a query result set.

14. The computer-readable medium of claim 13, wherein the operations further comprise:

receiving user input selecting the abstract rule; and

displaying a query creation form to the user, the form being configured to guide the user through selection of suitable result fields for a query against a database, the suitable result fields requesting for the one or more field values.

15. The computer-readable medium of claim 14, wherein the suitable result fields correspond to fields included in the conditional statement and needed to resolve the conditional statement.

16. The computer-readable medium of claim 11, wherein the operations further comprise:

executing a query against a database;

receiving a result set for the executed query; and

determining, from the result set, one or more inputs against which the conditional statement is resolved;

wherein the transformed rule includes the inputs.

17. The computer-readable medium of claim 11, wherein retrieving the abstract rule is done in response to running an analysis routine referencing the abstract rule;

and wherein the returned particular recommendation is an analysis result for the analysis routine.

18. The computer-readable medium of claim 11, wherein transforming the abstract rule into the transformed rule comprises:

retrieving a specification of the abstract rule in a first computer-readable language; and

transforming the specification into a language which is accepted by the rules engine.

19. The computer-readable medium of claim 18, wherein the first computer-readable language is XML and/or the language which is accepted by the rules engine is ABLE Rule Language.

20. A computer-readable medium containing a program which, when executed by a processor, performs operations for creating an abstract rule, the operations comprising:

creating a conditional statement using logical field definitions defined in an abstraction model that models underlying physical data in a manner making a schema of the physical data transparent to a user of the abstraction model;

creating, using the logical fields of the abstraction model, a consequential statement that defines a particular recommendation that is returned when the conditional statement is satisfied; and

associating the conditional statement with the consequential statement to generate the abstract rule.