System and method for metadata extraction, mapping and execution

• US 9,501,696 B1
• Filed: 02/09/2016
• Issued: 11/22/2016
• Est. Priority Date: 02/09/2016
• Status: Active Grant

• Current Assignee: Roberto Rosario, William Caban
• Original Assignee: William Caban
• Inventors: Cabn, William, Rosario, Roberto
• Primary Examiner(s): Dang, Duy M
• Application Number:
  US15/019,164
• Time in Patent Office: 287 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/51 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/583 using metadata automatically derived from the content
• CPC Class Codes: G06V 10/22 by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables

Abstract

The present disclosure provides a system and method for mapping zone-based metadata into one or more reference-able objects. The system and method extracts and/or generates metadata from a document according to custom zones defined in a document type. Each custom zone is associated to actions such as generating events, invoking triggers and/or invoking callback methods. One or more of these actions may be triggered when pre-processing or post-processing a document. According to an inventive concept of the present application, when a document is stored in a data storage and placed in a process queue to be processed by a suitable processing plugin according to the custom zones defined in the document. For instance, an image file comprising textual custom zones may be processed by an OCR plugin which extracts text metadata from the document. Other processing plugins include plugins to extract metadata from proprietary document formats such as CAD, PPTX, PDF, PSD, or others. Plugins are also available for generation of metadata by interpreting an image (i.e. detection or identification of objects and/or scenery in an image) through artificial intelligence and computer vision means. The process queue can be used for scalability of the quantity of actions to process.

Claims

1. A zone-based metadata extraction method comprising:

storing a document type comprising a plurality of zones;

assigning one or more triggers to one or more zones in the plurality of zones;

receiving a document associated with the document type;

storing the document in a queue service;

notifying a first plugin service associated to the one or more zones in the plurality of zones;

extracting, by the first plugin service, a first metadata element associated to the one or more zones in the plurality of zones;

assigning the first metadata element to one or more objects associated to the document type;

storing the one or more objects associated to the document type; and

,

invoking the one or more triggers assigned to the one or more zones in the plurality of zones.

2. The zone-based metadata extraction method of claim 1, further comprising:

notifying a second plugin service associated to the one or more zones in the plurality of zones;

extracting, by the second plugin service, a second metadata element associated to the one or more zones in the plurality of zones;

assigning the second metadata element to the one or more objects associated to the document type;

storing the one or more objects associated to the document type; and

,

invoking the one or more triggers assigned to the one or more zones in the plurality of zones.

3. The zone-based metadata extraction method of claim 2, wherein the document associated with the document type comprises text and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises applying optical character recognition to the document associated with the document type.

4. The zone-based metadata extraction method of claim 2, wherein the document associated with the document type comprises wherein the document associated with the document type is a file in a binary format and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction from the binary format.

5. The zone-based metadata extraction method of claim 2, wherein the document associated with the document type is an image file and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction using computer vision.

6. The zone-based metadata extraction method of claim 2, wherein the document associated with the document type is a file in a native format and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction from the native format.

7. A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to:

store a document type comprising a plurality of zones;

assign one or more triggers to one or more zones in the plurality of zones;

receive a document associated with the document type;

store the document in a queue service;

notify a first plugin service associated to the one or more zones in the plurality of zones;

extract, by the first plugin service, a first metadata element associated to the one or more zones in the plurality of zones;

assign the first metadata element to one or more objects associated to the document type;

store the one or more objects associated to the document type; and

,

invoke the one or more triggers assigned to the one or more zones in the plurality of zones.

8. The computer-readable storage medium of claim 7, wherein the instructions further configure the computer to:

notify a second plugin service associated to the one or more zones in the plurality of zones;

extract, by the second plugin service, a second metadata element associated to the one or more zones in the plurality of zones;

assign the second metadata element to the one or more objects associated to the document type;

store the one or more objects associated to the document type; and

,

invoke the one or more triggers assigned to the one or more zones in the plurality of zones.

9. The computer-readable storage medium of claim 8, wherein the document associated with the document type comprises text and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises apply optical character recognition to the document associated with the document type.

10. The computer-readable storage medium of claim 8, wherein the document associated with the document type is a file in a binary format and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction from the binary format.

11. The computer-readable storage medium of claim 8, wherein the document associated with the document type is an image file and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction using computer vision.

12. The computer-readable storage medium of claim 8, wherein the document associated with the document type is a file in a native format and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction from the native format.

13. A computing system, the computing system comprising:

a first processor;

a second processor;

an object and metadata storage;

a metadata storage; and

a first memory storing instructions that, when executed by the first processor, configure the system to;

store a document type comprising a plurality of zones in the object and metadata storage;

assign one or more triggers to one or more zones in the plurality of zones;

receive a document associated with the document type;

store the document in a queue service;

notify a first plugin service associated to the one or more zones in the plurality of zones;

a second memory storing instructions that, when executed by the second processor, configure the system to;

extract, by the first plugin service, a first metadata element associated to the one or more zones in the plurality of zones;

assign the first metadata element to one or more objects associated to the document type;

store the one or more objects associated to the document type in the metadata storage; and

,

invoke the one or more triggers assigned to the one or more zones in the plurality of zones.

14. The computing system of claim 13, further comprising:

a third processor;

the first memory storing instructions, when executed by the first processor, further configure the system to notify a second plugin service associated to the one or more zones in the plurality of zones; and

,

a third memory storing instructions that, when executed by the third processor, configure the system to;

extract, by the second plugin service, a second metadata element associated to the one or more zones in the plurality of zones;

assign the second metadata element to the one or more objects associated to the document type;

store the one or more objects associated to the document type in the metadata storage; and

,

invoke the one or more triggers assigned to the one or more zones in the plurality of zones.

15. The computing system of claim 14, wherein the document associated with the document type comprises text and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises apply optical character recognition to the document associated with the document type.

16. The computing system of claim 14, wherein the document associated with the document type is a file in a binary format and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction from the binary format.

17. The computing system of claim 14, wherein the document associated with the document type is an image file and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction use computer vision.

18. The computing system of claim 14, wherein the document associated with the document type is a file in a native format and wherein extracting the first metadata element or the second metadata element associated to each zone in the plurality of zones comprises metadata extraction from the native format.

19. The computing system of claim 13, wherein the second memory storing instructions that, when executed by the second processor, further configure the system to replicate the metadata stored in the metadata storage to the object and metadata storage.