Knowledge automation engine for product knowledge management

• US 20030149677A1
• Filed: 12/13/2002
• Published: 08/07/2003
• Est. Priority Date: 08/04/2000
• Status: Abandoned Application

• Current Assignee: Sun Microsystems Incorporated (Oracle Corporation)
• Original Assignee: Sun Microsystems Incorporated (Oracle Corporation)
• Inventors: Bingham, Paris E. Jr., Martin, Rex G., Treece, Alan J., Helgren, Matthew J., Little, Mike E.
• Application Number:
  US10/318,707
• Publication Number:
  US 20030149677A1
• Time in Patent Office: Days
• US Class Current: 706/45
• CPC Class Codes: G06F 11/2257 using expert systems
• CPC Class Codes: G06F 8/61 Installation
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models
• CPC Class Codes: G06N 5/025 Extracting rules from data

Abstract

A knowledge automation engine to use in detecting product issues on products. A knowledge automation engine may evaluate a check against a fact to detect a product issue on a product and provide a user of the product remediation information. A check may contain a product issue description, a rule to evaluate against a fact in order to detect the product issue, and remediation information to help a user address the product issue if the product issue is detected on the product. Product issues may include product installation validation and known product bugs. Facts used by the knowledge automation engine may include product configuration facts.

Claims

1. A system, comprising:

a processor

a memory coupled to the processor and configured to store program instructions executable by the processor to implement;

a knowledge automation engine comprising;

a knowledge interface to receive one or more checks from a knowledge repository;

a fact interface to receive one or more facts describing a product configuration;

wherein the knowledge automation engine automatically evaluates a rule in the one or more checks against the one or more facts to determine if any product issues specified by the one or more checks exists for the product configuration; and

wherein if the product issue is detected, the knowledge automation engine provides the remediation information as output.

2. The system as recited in claim 1, further comprising selecting the one or more checks from the knowledge repository using a keyword associated with each check;

wherein the keyword indicates a type of product issue detectable by the check.

3. The system as recited in claim 1, wherein the knowledge automation engine retrieves a fact from a fact repository to use in executing the rule in the check.

4. The system as recited in claim 1, wherein the knowledge automation engine retrieves a fact from a fact collector;

wherein the fact collector finds facts not in the fact repository and needed to execute the rule in the check.

5. The system as recited in claim 1, wherein the knowledge automation engine retrieves a fact from a user of the product to use in executing the rule in the check.

6. The system as recited in claim 5, wherein receiving a fact from a user further comprises instructing the user to perform a set of instructions and instructing the user to input the resulting fact.

7. The system as recited in claim 1, further comprising executing an applicability rule in the check to determine if the check is applicable to the product before executing a condition rule in the check;

wherein the condition rule is executed against a fact to determine if the product issue is present.

8. The system as recited in claim 7, further comprising if more than one check is received by the knowledge automation engine, the knowledge automation engine executes the applicability rule of each check received before executing the condition rule of any check received.

9. The system as recited in claim 1, wherein the remediation information returned by the knowledge automation engine includes a severity level, product issue analysis, product issue recommendation, and reference document list.

10. The system as recited in claim 1, wherein the knowledge automation engine is self contained in an application running on a user product;

wherein the knowledge automation engine receives a set of checks from knowledge repository using a network.

11. The system as recited in claim 1, wherein the knowledge automation engine is accessible by a product over a network;

wherein the knowledge automation engine detects a product issue on a product using facts about the product configuration sent by the product over the network.

12. The system as recited in claim 1, wherein the rule in the check is in a knowledge predicate language and the knowledge automation engine comprises a rules interpreter to execute the knowledge predicate language to detect the product issue associated with the check.

13. The system as recited in claim 1, wherein the check has a plurality of rules.

14. A method, comprising:

searching for a check in a knowledge repository;

wherein the check comprises a rule to detect a product issue for one or more products and remediation information for the product issue;

receiving the check from the knowledge repository;

evaluating the rule in the check against a fact to determine if a product issue is present on a product;

if the fact needed to evaluate the check exists in a fact repository, receiving the fact needed to evaluate the check from the fact repository;

if a fact needed to evaluate the check does not exist in the fact repository, sending a query for the fact to a facts collector coupled to an input source and receiving the fact from the facts collector if the fact is found by the facts collector; and

if evaluating the check detects the product issue, returning the remediation information for the product issue.

15. The method as recited in claim 14, wherein the searching for a check includes searching a description section in the check for an indication that the check is related to a particular type of product issue.

16. The method as recited in claim 14, wherein the check received has an applicability rule formatted according to a rule language and a condition rule formatted according to a rule language;

wherein the applicability rule is evaluated by a knowledge automation engine to determine if the check is related to relevant product characteristics and the condition rule is evaluated by the knowledge automation engine to detect a product issue on the product.

17. The method as recited in claim 14, wherein the facts collector further comprises a personal digital assistant interface used by a technician repairing the product.

18. The method as recited in claim 14, further comprising returning remediation information in the check when evaluating the check against the fact detects the product issue;

wherein the remediation information addresses the product issue.

19. The method as recited in claim 14, further comprising collecting statistical information on the checks run on a product;

wherein the statistical information is saved into a central database.

20. The method as recited in claim 19, wherein the statistical information is used to make product updates and predict product issues on other products.

21. The method as recited in claim 14, wherein receiving the checks further comprises receiving the checks over a network by a knowledge automation engine embedded in the product;

wherein the knowledge automation engine evaluates the checks locally on the product.

22. A carrier medium comprising program instructions, wherein the program instructions are computer-executable to:

searching for a check in a knowledge repository;

wherein the check comprises a rule to detect a product issue for one or more products and remediation information for the product issue;

receiving the check from the knowledge repository;

evaluating the rule in the check against a fact to determine if a product issue is present on a product;

if the fact needed to evaluate the check exists in a fact repository, receiving the fact needed to evaluate the check from the fact repository;

if a fact needed to evaluate the check does not exist in the fact repository, sending a query for the fact to a facts collector coupled to an input source and receiving the fact from the facts collector if the fact is found by the facts collector; and

if evaluating the check detects the product issue, returning the remediation information for the product issue.

23. The carrier medium as recited in claim 22, wherein the searching for a check includes searching a description section in the check for an indication that the check is related to a particular type of product issue.

24. The carrier medium as recited in claim 22, wherein the check received has an applicability rule formatted according to a rule language and a condition rule formatted according to a rule language;

wherein the applicability rule is evaluated by a knowledge automation engine to determine if the check is related to relevant product characteristics and the condition rule is evaluated by the knowledge automation engine to detect a product issue on the product.

25. The carrier medium as recited in claim 22, wherein the facts collector further comprises a personal digital assistant interface used by a technician repairing the product.

26. The carrier medium as recited in claim 22, further comprising returning remediation information in the check when evaluating the check against the fact detects the product issue;

wherein the remediation information addresses the product issue.

27. The carrier medium as recited in claim 22, further comprising collecting statistical information on the checks run on a product;

wherein the statistical information is saved into a central database.

28. The carrier medium as recited in claim 27, wherein the statistical information is used to make product updates and predict product issues on other products.

29. The carrier medium as recited in claim 22, wherein receiving the checks further comprises receiving the checks over a network by a knowledge automation engine embedded in the product;

wherein the knowledge automation engine evaluates the checks locally on the product.