System and method for networked decision making support

• US 20070061128A1
• Filed: 09/09/2005
• Published: 03/15/2007
• Est. Priority Date: 09/09/2005
• Status: Active Grant

• Current Assignee: Rateze Remote Mgmt. L.L.C. (Intellectual Ventures LLC)
• Original Assignee: Kang Jo Mgmt LLC (Intellectual Ventures LLC)
• Inventors: Way, Robert, Odom, Paul
• Granted Patent: US 8,433,711 B2
• Time in Patent Office: Days
• US Class Current: 704/4
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The present invention provides systems and methods for decision making support. The decision making support can be used, for example, for help desk troubleshooting, medical diagnosis, financial planning, and expert device. The decision support system of the invention includes a processor and a memory having a decision support program module, a phase dictionary, one or more solution nodes and optionally a topic identification information module. The decision support module is configured to enable the processor to receive a problem constraint and one or more user-specified phrases, which are then used to search nodes in a solution domain to identify a set of nodes potentially related to the user'"'"'s problem or question. The set of nodes potentially related to the user'"'"'s problem or question are ranked and displayed. Methods to determine potential solution nodes and to update solution nodes within the decision support system are provided.

Claims

1. A method for identifying a set of potentially related diagnoses and questions related to a problem in a solution domain having a plurality of nodes, wherein each node includes a plurality of phrases, comprising:

(a) receiving a constraint;

(b) searching the plurality of nodes to generate a first set of potentially related nodes, wherein each node in the first set of potentially related nodes includes the constraint;

(c) generating a first phrase list, wherein the first phrase list includes one or more phrases contained within the first set of potentially related nodes, wherein the first phrase list includes a set of potentially related physical characteristics, diagnoses, and problem statement phrases;

(d) receiving one or more user-specified phrases;

(e) searching the plurality of nodes to generate a second set of potentially related nodes, wherein each node in the second set of potentially related nodes includes the constraint or any of the one or more user-specified phrases; and

(f) generating a second phrase list, wherein the second phrase list includes one or more phrases.

2. The method of claim 1, wherein the one or more user-specified phrases are a subset of the plurality of phrases in the first phrase list.

3. The method of claim. 1, wherein each node includes a plurality of potential responses to information presented in the node.

4. The method of claim 3, wherein the one or more user-specified phrases include at least one of the plurality of responses in a node.

5. The method of claim 1, wherein each node further comprises:

a short description;

a type indicator; and

one or more topics that relate to the node.

6. The method of claim 5, wherein step (c) includes:

(i) retrieving the one or more phrases from a node in the first set of potentially related nodes to generate a first set of phrases;

(ii) removing redundant phrases from the first set of phrases to generate a second set of phrases; and

(iii) ordering the second set of phrases.

7. The method of claim 6, wherein step (iii) includes:

ordering the phrases alphabetically.

8. The method of claim 6, further comprising separating the second set of phrases into one or more categories.

9. A method for identifying a set of diagnoses and questions potentially related to a problem in a solution domain having a plurality of nodes, wherein each node includes a plurality of phrases, comprising:

(a) receiving a constraint and one or more user-specified phrases;

(b) identifying an inverse for each of the one or more user-specified phrases;

(c) searching the plurality of nodes to generate a first set of potentially related nodes, wherein the search selects nodes that include the constraint or any of the one or more user-specified phrases; and

(d) removing nodes from the first set of solution nodes that include the inverse of any of the one or more user-specified phrase to generate a second set of potentially related nodes.

10. The method of claim 9, further comprising:

(e) ranking the nodes in the second set of potentially related nodes.

11. The method of claim 10, wherein step (e) further comprises:

for one or more nodes in the second set of potentially related nodes,

(i) determining the number of phrases that match any of the one or more user-specified phrases;

(ii) determining the number of phrases that do not match any of the one or more user-specified phrases;

(iii) multiplying the number of matched phrases by a first weight to generate a matched value;

(iv) multiplying the number of matched phrases by a second weight to generate an unmatched value; and

(v) subtracting the unmatched value from the matched value to generate a weighted score for the node.

12. The method of claim 11, wherein step (e) further comprises ranking the nodes in the second set of potentially related nodes in ascending or descending order of weighted scores.

13. The method of claim 10, further comprising:

(f) receiving one or more additional user-specified phrases; and

(g) repeating steps (b) through (f) until the second set of potentially related nodes has been sufficiently narrowed.

14. The method of claim 9, further comprising:

(e) incrementing a success counter associated with a node identified as the proper diagnosis of the problem.

15. The method of claim 10, further comprising:

(i) adjusting the ranking of the nodes in the second set of potentially related nodes using a success counter associated with each node in the second set of potentially related nodes.

16. The method of claim 9, further comprising:

prior to step (a), generating topics associated the plurality of nodes in the solution domain, wherein a topic is a word or word combination that occurs a statistically significant number of times in a node.

17. The method of claim 16, further comprising:

(e) determining whether the constraint includes a word combination that is a topic.

18. The method of claim 17, wherein if the constraint includes a word combination that is a topic, the search of step (c) selects nodes that include the words in the word combination of the constraint contiguously.

19. The method of claim 17, wherein if the constraint includes a word combination that is a topic, the search of step (c) selects nodes that include the words in the word combination of the constraint separated by a specified number of words.

20. The method of claim 16, further comprising:

determining the frequency that each topic occurs within a node.

21. The method of claim 20, further comprising:

if the second set of potential nodes is empty,

(e) comparing each word and word combination in the constraint to the topics;

(f) determining the frequency of occurrence for each word and word combination in the constraint;

(g) modifying the constraint to remove the word or word combination having the lowest frequency of occurrence; and

(h) repeating steps (c) and (d).

22. The method of claim 9, further comprising:

if the second set of potentially related nodes is empty,

(e) investigating the problem off-line to identify a diagnosis for the problem;

(f) entering a new node to the domain, wherein the new node includes the diagnosis determined in step (e); and

(g) integrating the new node into the domain.

23. A system for providing a set of diagnoses and questions potentially related to a problem in a solution domain, comprising:

a processor; and

a memory coupled to the processor, wherein the memory includes;

a plurality of nodes, wherein one or more nodes includes one or more phrases,

a decision support program module configured to enable a processor to receive a constraint and one or more user-specified phrases and to search the plurality of nodes to identify a first set of potentially related nodes that include the constraint or any of the one or more user-specified phrases.

24. The system of claim 23, wherein each node further includes one or more potential responses to information presented in the node.

25. The system of claim 23, wherein the decision support program module is further configured to enable the processor to rank the nodes in the first set of potentially related nodes according to their likelihood of solving the problem.

26. The system of claim 23, wherein the decision support program module is further configured to enable the processor to display a phrase list and the first set of potentially related nodes, wherein the phrase list includes one or more phrases retrieved from the first set of potentially related nodes.

27. The system of claim 26, wherein the decision support program module is further configured to enable the processor to receive at least one additional user-specified phrase and to generate a second set of potentially related nodes using the constraint, the one or more user specified phrases, and the at least one additional user-specified phrase.

28. The system of claim 26, wherein the at least one additional user-specified phrase is a subset of the one or more solution phrases in the phrase list.

29. The system of claim 28, wherein the at least one additional user-specified phrase is a response in the one or more responses of a node in the first set of potentially related nodes.

30. The system of claim 24, wherein the memory further includes a phrase dictionary, wherein the phrase dictionary includes an inverse of each of the one or more phrases defined for the system.

31. The system of claim 30, wherein the decision support program module is further configured to enable the processor to remove nodes from the first set of potentially related nodes that include any inverse of the one or more user-specified phrases.

32. The system of claim 23, wherein the decision support system is a system selected from the group of a hardware troubleshooting system, a software troubleshooting system, a medical diagnosis system, a financial planning system, and an expert advice system.

33. A method for identifying a set of potentially related diagnoses and questions related to a problem in a solution domain having a plurality of nodes, wherein each node includes a plurality of phrases, comprising:

(a) receiving a constraint;

(b) searching the plurality of nodes to generate a first set of potentially related nodes, wherein each node in the first set of potentially related nodes includes the constraint; and

(c) generating a first phrase list, wherein the first phrase list includes one or more phrases contained within the first set of potentially related nodes, wherein the first phrase list includes a set of potentially related physical characteristics, diagnoses, and problem statement phrases.