Content based recommendations of file system save locations

Patent metadata

Field	Value
Publication number	US-11119979-B2
Application number	US-201816049005-A
Country	US
Kind code	B2
Filing date	Jul 30, 2018
Priority date	Jul 30, 2018
Publication date	Sep 14, 2021
Grant date	Sep 14, 2021

Abstract

Systems and methods for content based routing are provided. Aspects include receiving, by a processor, a request to save a file. Analyzing, by the processor, data associated with the file. Determining one or more file save locations for the file based on a feature vector, generated by a machine learning model, comprising a plurality of features extracted from the data associated with the file and presenting the one or more file save locations to a user.

First claim

What is claimed is:

1. A computer-implemented method for content based routing, the method comprising:
receiving, by a processor, a request to save a file;
analyzing using natural language processing (NLP), by the processor, data associated with the file, wherein the data comprises content of the file, wherein the content is music data;
analyzing using sentiment analysis, by the processor, a file directory to determine one or more file save locations having one or more other files with similar music data to the music data of the file; and
presenting, via a graphical user interface, the one or more file save locations to a user.

2. The computer-implemented method of claim 1 , further comprising:
receiving, by the processor through the graphical user interface, an input from the user responsive to presenting the one or more file save locations, wherein the input comprises a selection of a designated file save location from the one or more file save locations; and
saving the file to the designated file save location based at least in part on the input from the user.

3. The computer-implemented method of claim 1 , further comprising:
receiving, by the processor through the graphical user interface, an input from the user responsive to presenting the one or more file save locations, wherein the input comprises an indication rejecting the one or more file save locations; and
updating the machine learning model based on the indication.

4. The computer-implemented method of claim 1 , wherein the data associated with the file further comprises metadata of the file.

5. The computer-implemented method of claim 1 further comprising generating, by the processor, a file name for the file, based at least in part on the data associated with the file.

6. The computer-implemented method of claim 1 , wherein the file is attached to an email in an email program, the email program executed by the processor; and
wherein the determining, by the processor, the one or more file save locations for the file is further based on data associated with the email in the email program.

7. The computer-implemented method of claim 1 further comprising creating, by the processor, a new file save directory for the file based on the data associated with the file.

8. A system for content based routing, the system comprising:
a processor communicatively coupled to a memory, the processor configured to:
receive a request to save a file;
analyze using natural language processing (NLP) data associated with the file, wherein the data comprises content of the file, wherein the content is music data;
analyze using sentiment analysis a file directory to determine one or more file save locations having one or more other files with similar music data to the music data of the file; and
present, via a graphical user interface, the one or more file save locations to a user.

9. The system of claim 8 , wherein the processor is further configure to:
receive, via a graphical user interface, an input from the user responsive to presenting the one or more file save locations, wherein the input comprises a selection of a designated file save location from the one or more file save locations; and
save the file to the designated file save location based at least in part on the input from the user.

10. The system of claim 8 , wherein the processor is further configure to:
receive, via a graphical user interface, an input from the user responsive to presenting the one or more file save locations, wherein the input comprises an indication rejecting the one or more file save locations; and
update the machine learning model based on the indication.

11. The system of claim 8 , wherein the data associated with the file further comprises metadata of the file.

12. The system of claim 8 wherein the processor is further configure to:
creating a file name for the file, based at least in part on the data associated with the file.

13. A computer program product for content based routing comprising a computer readable storage medium having program instructions embodied therewith, where the program instructions are executable by a processor to cause the processor to perform a method comprising:
receiving, by the processor, a request to save a file;
analyzing using natural language processing (NLP), by the processor, data associated with the file, wherein the data comprises content of the file, wherein the content is music data;
analyzing using sentiment analysis, by the processor, a file directory to determine one or more file save locations having one or more other files with similar music data to the music data of the file; and
presenting, via a graphical user interface the one or more file save locations to a user.

14. The computer program product of claim 13 , further comprising:
receiving, by the processor through the graphical user interface, an input from the user responsive to presenting the one or more file save locations, wherein the input comprises a selection of a designated file save location from the one or more file save locations; and
saving the file to the designated file save location based at least in part on the input from the user.

15. The computer program product of claim 13 , further comprising:
receiving, by the processor through the graphical user interface, an input from the user responsive to presenting the one or more file save locations, wherein the input comprises an indication rejecting the one or more file save locations; and
updating the machine learning model based on the indication.

16. The computer program product of claim 13 , wherein the data associated with the file further comprises metadata of the file.

17. The computer program product of claim 13 further comprising generating a file name for the file, based at least in part on the data associated with the file.

Assignees

• IBM

Inventors

• Lapointe Michael
• Natesan Jayapreetha
• Saha Chanchal
• Stanquist Gerald
• Hirst Jason
• Finch Richard B

Classifications

• G06N3/065

  Analogue means · CPC title

• G06N5/01

  Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound · CPC title

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06F16/16 Primary

  File or folder operations, e.g. details of user interfaces specifically adapted to file systems · CPC title

• G06F16/13 Primary

  File access structures, e.g. distributed indices (arrangements of input from, or output to, record carriers G06F3/06) · CPC title