Decision-theoretic methods for identifying relevant substructures of a hierarchical file structure to enhance the efficiency of document access, browsing, and storage

• US 7,039,642 B1
• Filed: 05/04/2001
• Issued: 05/02/2006
• Est. Priority Date: 05/04/2001
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Horvitz, Eric J., Koch, Paul
• Primary Examiner(s): Wong, Leslie
• Application Number:
  US09/849,644
• Time in Patent Office: 1,824 Days
• Field of Search: 707 1- 10, 707100-1041, 709/218, 709/223
• US Class Current: 1/1
• CPC Class Codes: G06F 16/10 File systems; File servers
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

A system and methodology is provided for improving directory operations within a system providing an electronic hierarchical directory of items. The system includes a component which analyzes probabilities and utilities associated with determining potential target directories for storing and accessing data, and a component for building a subset of the potential target directories that are predicted to be the target directory. The probabilities and/or utilities are functions of expected navigation costs associated with traversing from a displayed directory to at least one of the potential target directories. Methods in accordance with the present invention can be coupled with displays of substructures that format the substructures into a coherent hierarchical view.

Claims

1. A computer implemented system for predicting a target file directory, comprising:

a first component that infers and/or determines expected navigation costs for directory operations associated with potential target directories, the expected navigation cost is based on a probabilistic and/or utility analysis that includes a list scan penalty for reducing probabilities associated with scanning lists within a directory; and

a second component that outputs a subset of the potential target directories to a display, the subset is determined by selecting target directories, based in part on the expected navigation cost, in order to minimize a cost of traversing directories.

2. The system of claim 1, the utilities are functions of navigation costs associated with traversing from a node associated with a potential target directory under consideration to at least one of the other potential target directories.

3. The system of claim 1, the second component further determines the subset of directories based on expected utilities, which are computed as functions of probabilities of target information being at a node, and the navigation costs associated with traversing from the node to at least one of the potential target directories.

4. The system of claim 2, the navigation costs are assigned by at least one of user selections and encoded within the system.

5. The system of claim 1, the potential target directories are determined from at least one of a local computer system and a remote computer system.

6. The system of claim 1, the probabilities are a function of recent and long-term file activity within a directory.

7. The system of claim 6, the long term file activity is determined from a predetermined time horizon.

8. The system of claim 6, the recent file activity is determined from frequency of access to a file.

9. The system of claim 8, further comprising a background monitor to determine file access frequency.

10. The system of claim 1, the list scan penalty is determined as an exponential function that decreases as the number of elements on the list increases.

23. The system of claim 1, the second component outputs the subset of directories as tree fragments.

24. The system of claim 1, the subset comprises N potential target directories, N is an integer that is predefined.

25. The system of claim 1, the subset comprises directories with expected navigation costs below a predetermined level.

11. A method effectuated at least in part by a machine for determining a potential target node for directory operations, comprising:

assigning probabilities and utilities to a plurality of potential target nodes, the utilities represent costs associated with navigating from a recommended node to an actual target node;

determining a list scan penalty for reducing the probabilities associated with scanning lists within a directory;

determining an expected utility from the probabilities and utilities associated with the plurality of target nodes; and

displaying a candidate list of likely nodes to a user based upon the expected utility.

12. The method of claim 11, further comprising multiplying the assigned probabilities and utilities together to form a product at each of the plurality of target nodes.

13. The method of claim 12, further comprising summing the products from each of the plurality of target nodes together to determine the expected utility for one of the plurality of potential target nodes.

14. The method of claim 11, the utilities are related to navigation costs associated with traversing from a displayed directory to at least one of the potential target directories.

15. The method of claim 14, the navigation costs are assigned by at least one of user selections and encoded within the system.

16. The method of claim 11, the potential target nodes are determined from at least one of a local computer system and a remote computer system.

17. The method of claim 11, the probabilities are a function of recent and long-term file activity within a directory.

18. The method of claim 17, the long-term file activity is determined from a predetermined time horizon.

19. The method of claim 17, the recent file activity is determined from frequency of access to a file.

20. The method of claim 19, further comprising,

monitoring a user to determine file access frequency.

21. The method of claim 11, the list scan penalty is determined as an exponential function that decreases as the number of elements on the list increases.

26. The method of claim 11, displaying the candidate list in descending order from highest expected utility.

27. The method of claim 13, further comprising removing a potential target node with a maximum expected utility from consideration when evaluating expected utility for the other potential target nodes.

22. A machine implemented system for determining a potential target node for directory operations, comprising:

means for assigning probabilities and utilities to a plurality of potential target nodes;

means for determining a list scan penalty for reducing the probabilities associated with scanning lists within a directory;

means for determining an expected utility from the probabilities and utilities associated with the plurality of target nodes; and

means for displaying a candidate list of likely nodes to a user based upon the expected utility, the candidate list comprises a subset of the potential target nodes.