Building, reusing and managing authored content for incident management

• US 8,892,539 B2
• Filed: 11/28/2012
• Issued: 11/18/2014
• Est. Priority Date: 11/28/2012
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Anand, Rangachari, Lee, Juhnyoung, Liu, Rong, Miyamoto, Kohtaroh
• Primary Examiner(s): To, Baoquoc N
• Application Number:
  US13/687,725
• Publication Number:
  US 20140149411A1
• Time in Patent Office: 720 Days
• Field of Search: 707/E17.068, 707999001-999009, 707/705
• US Class Current: 707/705
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/35 Clustering; Classification

Abstract

Building, reusing and calibrating network of authored content, in one aspect, may comprise clustering a plurality of problem tickets into one or more clusters. The clusters may be associated to one or more FAQ nodes in a FAQ network. The associated one or more FAQ nodes may be checked to determine whether the nodes are part of a broken branch. If the one or more FAQ nodes leads to a broken branch, a user may be notified to update the branch, e.g., with an answer or resolution to the one or more FAQ nodes.

Claims

1. A method for building, reusing and calibrating network of authored content, comprising:

receiving a plurality of problem tickets;

clustering, by a processor, the plurality of problem tickets into one or more clusters;

associating, by the processor, the one or more clusters to one or more FAQ nodes in a FAQ network;

determining, by the processor, whether the one or more FAQ nodes is part of a broken branch; and

notifying a user of the broken branch.

2. The method of claim 1, further comprising:

receiving an answer corresponding to the one or more FAQ nodes; and

updating the broken branch with the answer.

3. The method of claim 1, wherein the clustering of the plurality of problem tickets into one or more clusters comprises:

performing facet data matching among a plurality of attributes associated with the problem tickets;

clustering by text data analysis among the problem tickets whose facet data matched; and

performing trend analysis on the clusters of tickets clustered by the text data analysis.

4. The method of claim 3, wherein the performing facet data matching, clustering by text data analysis, and performing trend analysis are processed in parallel.

5. The method of claim 1, wherein the associating the one or more clusters comprises scoring the one or more clusters and associating the one or more clusters to the one or more FAQ nodes in the FAQ network according to the scoring.

6. The method of claim 1, further comprising computing criticality of the one or more clusters, and the associating the one or more clusters comprises associating the one or more clusters that meet a threshold of criticality to the one or more FAQ nodes.

7. The method of claim 1, further comprising:

receiving a list of keywords;

matching the keywords with one or more nodes of the FAQ network;

determining a paths of the nodes in the FAQ network; and

returning the determined paths.

8. The method of claim 1, further comprising:

receiving an update request from a user;

identifying an expertise area of the user;

searching the FAQ network for an FAQ node containing an FAQ associated with the expertise area of the user; and

returning the FAQ to the user.

9. A system for building, reusing and calibrating network of authored content, comprising:

a computer processor;

a ticket analyzer operable to execute on the computer processor and further operable to determine frequently asked question candidates as content for authoring from a problem ticket description associated with an information technology system, the ticket analyzer further operable to progressively refine and refactor an FAQ network comprising the determined frequently asked question candidates as nodes in the FAQ network, the ticket analyzer further operable to provide a broken branch, manage FAQ network with criticality of broken branch and associated tickets;

an authoring system for allowing one or more users to author answers to the frequently asked question candidates; and

an authored content user portal operable to allow the one or more users to locate frequently asked questions in the FAQ network to solve a problem.

10. The system of claim 9, wherein the ticket analyzer further comprises a FAQ matching module operable to obtain strongest paths of FAQ.

11. The system of claim 10, wherein the ticket analyzer further comprises a criticality calculator operable to calculate the criticality of the ticket.

12. The system of claim 11, wherein the ticket analyzer further comprises a cluster matching module operable to update cluster information and its scores and also update the FAQ network with ticket information.

13. A non-transitory computer readable storage medium storing a program of instructions executable by a machine to perform a method of building, reusing and calibrating network of authored content, comprising:

receiving a plurality of problem tickets;

clustering the plurality of problem tickets into one or more clusters;

associating the one or more clusters to one or more FAQ nodes in a FAQ network;

determining whether the one or more FAQ nodes is part of a broken branch; and

notifying a user of the broken branch.

14. The non-transitory computer readable storage medium of claim 13, further comprising:

receiving an answer corresponding to the one or more FAQ nodes; and

updating the broken branch with the answer.

15. The non-transitory computer readable storage medium of claim 13, wherein the clustering of the plurality of problem tickets into one or more clusters comprises:

performing facet data matching among a plurality of attributes associated with the problem tickets;

clustering by text data analysis among the problem tickets whose facet data matched; and

performing trend analysis on the clusters of tickets clustered by the text data analysis.

16. The non-transitory computer readable storage medium of claim 13, wherein the associating the one or more clusters comprises scoring the one or more clusters and associating the one or more clusters to the one or more FAQ nodes in the FAQ network according to the scoring.

17. The non-transitory computer readable storage medium of claim 13, further comprising computing criticality of the one or more clusters, and the associating the one or more clusters comprises associating the one or more clusters that meet a threshold of criticality to the one or more FAQ nodes.

18. The non-transitory computer readable storage medium of claim 13, further comprising:

receiving a list of keywords;

matching the keywords with one or more nodes of the FAQ network;

determining a paths of the nodes in the FAQ network; and

returning the determined paths.

19. The non-transitory computer readable storage medium of claim 13, further comprising:

receiving an update request from a user;

identifying an expertise area of the user;

searching the FAQ network for an FAQ node containing an FAQ associated with the expertise area of the user; and

returning the FAQ to the user.