Organically ranked knowledge categorization in a knowledge management system

1. In a knowledge management system, a method for organically ranked knowledge and categorization, the method comprising:

bookmarking answer content by adding the answer content to favorites for a first end user of the knowledge management system executing in memory of a computer;

suggesting a set of categories previously associated with the answer content by other end users of the knowledge management system in response to the first end user bookmarking answer content;

determining whether the first end user selected a category from the suggested set of categories or whether the first end user selected a new category;

upon determining the first end user selected the new category, creating the new category and also categorizing the bookmarked answer content according to the new category; and,

upon determining the first end user selected the category from the suggested set of categories, categorizing the bookmarked answer content with a category selected from the set of categories.

2. The method of claim 1 , wherein suggesting the set of categories previously associated with the answer content by other end users of the knowledge management system in response to the first end user bookmarking answer content, comprises:

sorting the set of categories previously associated with the answer content by other end users of the knowledge system according to a rank order determined by self-learning scores for each of the categories; and,

presenting the sorted set of categories to the first end user.

3. The method of claim 2 , further comprising adjusting the self-learning scores for the categories to account for the selected category.

4. The method of claim 1 , wherein suggesting the set of categories previously associated with the answer content by other end users of the knowledge management system in response to the first end user bookmarking answer content comprises weighting different ones of the self-learning scores to account for category selections by expert end users of the knowledge management system.

5. The method of claim 1 , further comprising:

comparing uncategorized answer content to already categorized content to identify similar answer content; and,

associating uncategorized answer content with categories already associated with similar categorized answer content.

6. The method of claim 1 , further comprising bookmarking additional answer content for the first end user already categorized with the selected category by the other end users of the knowledge management system.

7. The method of claim 1 , further comprising:

monitoring re-categorization of answer content; and,

notifying selected ones of the end users linked to categories from which a threshold amount of answer content has been re-categorized.

8. A knowledge management data processing system comprising:

a computer with at least one processor and memory;

a data store of categorizations coupled to the computer and comprising records associating answer content in the knowledge management data processing system with end user applied categories;

an expert modeler coupled to the data store, the expert modeler executing in the memory of the computer and configured to apply a ranked order to sub-sets of categories in the data store of categorizations according to self-learning scores applied to the categories; and,

organic ranked knowledge categorization logic comprising program code enabled when executed by the at least one processor of the computer to detect the bookmarking of answer content, bookmarking comprising adding answer content to favorites of an en user, to suggest a set of categories previously associated with end user bookmarked answer content by other end users of the knowledge management system in response to the end user bookmarking answer content, to determine whether the first end user selected a category from the suggested set of categories or whether the first end user selected a new category, upon determining the first end user selected the new category, to create the new category and also categorizing the bookmarked answer content according to the new category and upon determining the first end user selected the category from the suggested set of categories, to categorize the bookmarked answer content with a category selected from the set of categories.

9. The system of claim 8 , wherein the self-learning scores are weighted to account for category selections by expert ones of the other end users.

10. The system of claim 8 , wherein the answer content are articles in the knowledge management system.

11. A knowledge management computer program product comprising a non-transitory computer usable medium embodying computer usable program code for organically ranked knowledge and categorization, the computer program product comprising:

computer usable program code for bookmarking answer content by adding the answer content to favorites for a first end user of a knowledge management system;

computer usable program code for suggesting a set of categories previously associated with the answer content by other end users of the knowledge management system in response to the first end user bookmarking answer content;

computer usable program code for determining whether the first end user selected a category from the suggested set of categories or whether the first end user selected a new category;

upon determining the first end user selected the new category, computer usable program code for creating the new category and also categorizing the bookmarked answer content according to the new category; and,

upon determining the first end user selected the category from the suggested set of categories, computer usable program code for categorizing the bookmarked answer content with a category selected from the set of categories.

12. The computer program product of claim 11 , wherein the computer usable program code for suggesting the set of categories previously associated with the answer content by other end users of the knowledge management system in response to the first end user bookmarking answer content, comprises:

computer usable program code for sorting the set of categories previously associated with the answer content by other end users of the knowledge system according to a rank order determined by self-learning scores for each of the categories; and,

computer usable program code for presenting the sorted set of categories to the first end user.

13. The computer program product of claim 12 , further comprising computer usable program code for adjusting the self-learning scores for the categories to account for the selected category.

14. The computer program product of claim 12 , wherein suggesting the set of categories previously associated with the answer content by other end users of the knowledge management system in response to the first end user bookmarking answer content comprises computer usable program code for weighting different ones of the self-learning scores to account for category selections by expert end users of the knowledge management system.

15. The computer program product of claim 12 , further comprising:

computer usable program code for comparing uncategorized answer content to already categorized content to identify similar answer content; and,

computer usable program code for associating uncategorized answer content with categories already associated with similar categorized answer content.

16. The computer program product of claim 11 , further comprising computer usable program code for bookmarking additional answer content for the first end user already categorized with the selected category by the other end users of the knowledge management system.

17. The computer program product of claim 11 , further comprising:

computer usable program code for monitoring re-categorization of answer content; and,

computer usable program code for notifying end users linked to categories from which a threshold amount of answer content has been re-categorized.