Automatically Reorganize Folder/File Visualizations Based on Natural Language-Derived Intent

• US 20180011868A1
• Filed: 07/08/2016
• Published: 01/11/2018
• Est. Priority Date: 07/08/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Allen, Corville O., Freed, Andrew R., Vrouwenvelder, Adrianus P.
• Granted Patent: US 10,657,098 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 16/11 File system administration, e.g. details of archiving or snapshots file system backup G06F11/14
• CPC Class Codes: G06F 16/14 Details of searching files based on file metadata
• CPC Class Codes: G06F 16/16 File or folder operations, e.g. details of user interfaces specifically adapted to file systems
• CPC Class Codes: G06F 16/168 Details of user interfaces specifically adapted to file systems, e.g. browsing and visualisation, 2d or 3d GUIs query results presentation G06F16/156
• CPC Class Codes: G06F 16/242 Query formulation
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 40/242 Dictionaries
• CPC Class Codes: G06F 40/295 Named entity recognition

Abstract

A method, system and computer-usable medium are disclosed for computing file system management. A corpus of content is processed to extract metadata associated with folders and files referenced by a directory structure. Natural Language Processing (NLP) operations are then performed on the corpus to generate concept and entity data associated with each folder and file, followed by performing Natural Language (NL) classification operations to generate intent classification data, which in turn is processed. to determine ranked, dominant intents for each folder and file. The corpus content, extracted metadata, concept and entity data, and ranked dominant intents are then processed to generate indexed content and term data. Application context data associated with an interaction is collected and processed to determine a user intent, which is then processed with the indexed content and term data to identify a corresponding folder and file, which in turn are provided to the user.

Claims

1. A computer-implemented method for computing file system management, comprising:

processing a corpus of content to extract metadata associated with individual folders and files referenced by a directory structure;

performing Natural Language Processing (NLP) operations on the corpus to generate concept and entity data associated with each folder and file;

performing Natural Language (NL) classification operations on each folder and file to generate intent classification data;

processing the intent classification data to determine ranked, dominant intents for each folder and file; and

indexing the content, the extracted metadata, the concept and entity data, and the ranked dominant intents to generate indexed content and term data.

2. The method of claim 1, further comprising:

detecting an interaction associated with a first user;

collecting application context data associated with the interaction;

processing the application context data to determine a user intent;

processing the user intent and the indexed content and term data to identify a folder and file corresponding to the user intent; and

providing a reference to the identified folder and file to the first user.

3. The method of claim 1, wherein the NLP operations comprise at least one of the group of:

domain clustering;

entity detection; and

identity resolution.

4. The method of claim 2, wherein the application context data comprises information associated with at least one of the group of:

a software application executing on a computing device used by the first user;

a file type associated with a software application executing on a computing device used by the first user;

an online chat session conducted between the first user and a second user;

an email exchange between the first user and a second user;

a browser application executing on a computing device used by the first user to access web-based content;

a search query submitted by first user; and

a response to a search query submitted by the first user.

5. The method of claim 2, further comprising:

processing the application context data to modify a visual attribute associated with the reference to the folder and file;

using the modified visual attribute as the reference to the folder and file.

6. The method of claim 2, further comprising:

processing the application context data and the user intent to generate a corresponding intent scoring value for each folder and file;

sorting the folders and files according to their respective intent scoring values; and

providing references to the folders and files to the first user in their sorted order.

7. A system comprising:

a processor;

a data bus coupled to the processor; and

a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code used for computing file system management and comprising instructions executable by the processor and configured for;

processing a corpus of content to extract metadata. associated with individual folders and files referenced by a directory structure;

performing Natural Language Processing (NLP) operations on the corpus to generate concept and entity data associated with each folder and file;

performing Natural Language (NL) classification operations on each folder and file to generate intent classification data;

processing the intent classification data to determine ranked, dominant intents for each folder and file; and

indexing the content, the extracted metadata, the concept and entity data, and the ranked dominant intents to generate indexed content and term data.

8. The system of claim 7, further comprising:

detecting an interaction associated with a first user;

collecting application context data associated with the interaction;

processing the application context data to determine a user intent;

processing the user intent and the indexed content and term data to identify a folder and file corresponding to the user intent; and

providing a reference to the identified folder and file to the first user.

9. The system of claim 7, wherein the NLP operations comprise at least one of the group of:

domain clustering;

entity detection; and

identity resolution.

10. The system of claim 8, wherein the application context data comprises information associated with at least one of the group of:

a software application executing on a computing device used by the first user;

a file type associated with a software application executing on a computing device used by the first user;

an online chat session conducted between the first user and a second user;

an email exchange between the first user and a second user;

a browser application executing on a computing device used by the first user to access web-based content;

a search query submitted by first user; and

a response to a search query submitted by the first user.

11. The system of claim 8, further comprising:

processing the application context data to modify a visual attribute associated with the reference to the folder and file;

using the modified visual attribute as the reference to the folder and file.

12. The system of claim 8, further comprising:

processing the application context data and the user intent to generate a corresponding intent scoring value for each folder and file;

sorting the folders and files according to their respective intent scoring values; and

providing references to the folders and files to the first user in their sorted order.

13. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:

processing a corpus of content to extract metadata associated with individual folders and files referenced by a directory structure;

performing Natural Language Processing (NLP) operations on the corpus to generate concept and entity data associated with each folder and file;

performing Natural Language (NL) classification operations on each folder and file to generate intent classification data;

processing the intent classification data to determine ranked, dominant intents for each folder and file; and

indexing the content, the extracted metadata, the concept and entity data, and the ranked dominant intents to generate indexed content and term data.

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

detecting an interaction associated with a first user;

collecting application context data associated with the interaction;

processing the application context data to determine a user intent;

processing the user intent and the indexed content and term data to identify a folder and file corresponding to the user intent; and

providing a reference to the identified folder and file to the first user.

15. The non-transitory, computer-readable storage medium of claim 13, wherein the NLP operations comprise at least one of the group of:

domain clustering;

entity detection; and

identity resolution.

16. The non-transitory, computer-readable storage medium of claim 14, wherein the application context data comprises information associated with at least one of the group of:

a software application executing on a computing device used by the first user;

a file type associated with a software application executing on a computing device used by the first user;

an online chat session conducted between the first user and a second user;

an email exchange between the first user and a second user;

a browser application executing on a computing device used by the first user to access web-based content;

a search query submitted by the first user; and

a response to a search query submitted by the first user.

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

processing the application context data to modify a visual attribute associated with the reference to the folder and file;

using the modified visual attribute as the reference to the folder and file.

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

processing the application context data and the user intent to generate a corresponding intent scoring value for each folder and file;

sorting the folders and files according to their respective intent scoring values; and

providing references to the folders and files to the first user in their sorted order.

19. The non-transitory, computer-readable storage medium of claim 13, wherein the computer executable instructions are deployable to a client system from a server system at a remote location.

20. The non-transitory, computer-readable storage medium of claim 13, wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis.