Method and system of determining a prioritized list of users related to a given goal

• US 8,825,561 B2
• Filed: 08/10/2009
• Issued: 09/02/2014
• Est. Priority Date: 08/10/2009
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bellamy, Rachel K. E., Burnett, Margaret M., Lawrance, Joseph A., Malkin, Peter K., Richards, John T., Williams, Clay E.
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): Traktovenko, Ilya
• Application Number:
  US12/538,419
• Publication Number:
  US 20110035343A1
• Time in Patent Office: 1,849 Days
• Field of Search: 706/11, 706/45, 706/62
• US Class Current: 706/11
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06F 40/00 Handling natural language data speech analysis or synthesis, speech recognition G10L
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 50/10 Services
• CPC Class Codes: G09B 7/04 characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying a further explanation

Abstract

A method and system of determining a prioritized list of one or more users related to a given goal obtaining a set of places, determine one or more future places an expert associated with a given goal is predicted to visit to accomplish the given goal, obtain a history of one or more places users have visited, determine one or more historical places from the history of one or more places that match the future places, and identify one or more users associated with the determined one or more historical places.

Claims

1. A method of determining a prioritized list of one or more users related to a given goal, comprising:

obtaining a set of places by a processor;

predicting probability of one or more future places a hypothetical expert associated with a given goal is likely to visit to accomplish the given goal, wherein a predicted path comprising said one or more future places is obtained based on information scent similarity between a bug report associated with the given goal and said set of future places, the information scent similarity places, the information scent similarity of the said future places computed using proximal scent relative to the bug report;

obtaining a history of one or more places users have visited, wherein one or more historical paths comprising said one or more places for each of the users is obtained;

selecting one or more historical places from the history of one or more places that match the future places; and

identifying one or more users, from said users, who previously traversed at least some of the future places in the predicted path, as a best fit user who can accomplish the given goal.

2. The method of claim 1, further including:

outputting the identified one or more users associated with the determined one or more historical places.

3. The method of claim 1, wherein the given goal is described in a text document.

4. The method of claim 1, wherein the set of places is obtained by analyzing a collection of text with respect to the given goal, wherein the set of places comprises locations in the text.

5. The method of claim 4, wherein the collection of text includes source code, wherein the set of places comprises at least line numbers of the source code.

6. The method of claim 4, wherein the collection of text includes requirements.

7. The method of claim 4, wherein the collection of text includes documentation.

8. The method of claim 1, wherein the given goal is fixing a computer system bug.

9. The method of claim 1, wherein the given goal is described in a bug report.

10. The method of claim 1, wherein the history of one or more places users have visited includes secondary information associated with the users.

11. The method of claim 10, wherein the secondary information includes a role of the users.

12. The method of claim 1, wherein the step of identifying includes:

identifying all users associated with the determined one or more historical places.

13. The method of claim 1, further including:

determining frequency of historical visits for each of the determined future places.

14. The method of claim 1, further including:

determining total number of historical visits for each of the determined future places.

15. The method of claim 1, further including:

visualizing the one or more future places and the historical places.

16. The method of claim 15, wherein the visualizing further includes showing paths for the one or more future places and the historical places.

17. The method of claim 1, further including:

establishing a recommended user interface for recommending one or more users to accomplish the given goal.

18. The method of claim 1, wherein the set of places comprises locations in a source code and the predicted probability is computed by simulating the hypothetical expert navigating through the source code following links based on scent.

19. A non-transitory program storage device readable by a machine, tangibly embodying a program of instructions executable by the machine to perform a method for determining a prioritized list of one or more users related to a given goal, comprising:

obtaining a set of places;

predicting probability of one or more future places a hypothetical expert associated with a given goal is likely to visit to accomplish the given goal, wherein a predicted path comprising said one or more future places is obtained based on information scent similarity between a bug report associated with the given goal and said set of future places, the information scent similarity of the said future places computed using proximal scent relative to the bug report;

obtaining a history of one or more places users have visited, wherein one or more historical paths comprising said one or more places for each of the users is obtained;

selecting one or more historical places from the history of one or more places that match the future places; and

identifying one or more users, from said users, who previously traversed at least some of the future places in the predicted path, as a best fit user who can accomplish the given goal.

20. The program storage device of claim 19, further including:

outputting the identified one or more users associated with the determined one or more historical places.

21. The program storage device of claim 19, wherein the given goal is described in a text document.

22. The program storage device of claim 19, wherein the set of places is obtained by analyzing a collection of text with respect to the given goal.

23. A system for determining a prioritized list of one or more users related to a given goal, comprising:

a processor;

historical model including a history of one or more places users have visited, wherein one or more historical paths comprising said one or more places for each of the users is obtained;

a predictive model operable to predict probability of one or more future places a hypothetical expert associated with a given goal is likely to visit to accomplish the given goal, wherein a predicted path comprising said one or more future places is obtained based on information scent similarity between a bug report associated with the given goal and said set of future places, the information scent similarity of the said future places computed using proximal scent relative to the bug report;

a matching module operable to execute on the processor and to select one or more historical places from the history of one or more places that match the future places,

the matching module further operable to identify one or more users, from said users, who previously traversed at least some of the future places in the predicted path as a best fit user who can accomplish the given goal; and

a user interface module operable to present the identified one or more users.