System and method integrating machine learning algorithms to enrich documents in a content management system
A system and method for integrating machine learning algorithms to enrich content items in a content management system. The content management system includes at least one processor, a transformation engine to execute one or more transformations on content items stored in the content management system, and a machine learning services to apply a machine learning algorithm to the content items based on the one or more transformations.
1 . A content management system comprising:
at least one processor in communication with a content server having one or more storage media devices for storing one or more content items;
a first machine learning transformation model; and a second machine learning transformation model;
a first content item being transformed from a first format to a second format, wherein the transforming is performed by application of the first machine learning transformation model and the second machine learning transformation model;
wherein the first machine learning transformation model generates an association between the first format and the second format;
the first machine learning transformation model invokes a transformation policy based on the association; and
the transformation policy is invoked to update the first content item or changes in the association.
2 . The system of claim 1 , wherein transformation from the first format to the second format results in updating the first content item from a first rendition to a second rendition.
3 . The system of claim 2 , wherein a mark-up interface is provided to receive the second rendition comprising optical character recognition data having mark-up and geometry information.
4 . The system of claim 2 wherein the second rendition comprises a transcription of a media file that includes speech or encoded human-readable textual file format or a text-based summarization that is shorter than the first content item.
5 . The system of claim 1 , wherein the first and the second machine learning transformation models are sequentially applied to transform the first content item from a first rendition to a second rendition.
6 . The system of claim 1 , wherein the first machine learning transformation model transforms the first content item from a first format to an intermediate format and the second machine learning transformation model transforms the first content item from the intermediate format to a second format.
7 . The system of claim 1 , wherein the content management system is configured to: create an association between the first content item and a stored rendition;
type the association based upon the type of transformation being performed; and
invoke a policy based upon the type of the association.
8 . The system of claim 1 , wherein the association is created for a transformation type between the first content item and a rendition created by the first machine learning transformation model.
9 . The system of claim 1 , wherein the transformation policy is invoked to update the first content item or changes in the association without fully transforming the first content item again; or
the transformation policy is invoked to update changes in the association.
10 . A method of managing content in a content management system comprising:
at least one processor in communication with a content server having one or more storage media devices for storing one or more content items;
a first machine learning transformation model; and a second machine learning transformation model;
the method comprising transforming a first content item from a first format to a second format, wherein the transforming is performed by application of the first machine learning transformation model and the second machine learning transformation model;
wherein the first machine learning transformation model generates an association between the first format and the second format;
the first machine learning transformation model invokes a transformation policy based on the association; and
the transformation policy is invoked to update the first content item or changes in the association.
11 . The method of claim 10 , wherein transformation from the first format to the second format results in updating the first content item from a first rendition to a second rendition.
12 . The method of claim 11 , wherein in response to a request for access to the first content item, the first content item is rendered in the second format without invoking a transformation event.
13 . The method of claim 11 , wherein the second rendition comprises a transcription of a media file that includes speech, or encoded human-readable textual file format.
14 . The method of claim 10 , wherein responsive to detecting a change in data associated with the first content item, the first and the second machine learning transformation models are sequentially applied to transform the first content item from a first rendition to a second rendition.
15 . The method of claim 10 , wherein the first machine learning transformation model transforms the first content item from a first format to an intermediate format and the second machine learning transformation model transforms the first content item from the intermediate format to a second format.
16 . The method of claim 10 , wherein the first machine learning transformation model and the second machine learning transformation model exclude performing optical text recognition.
17 . A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:
servicing a first content item having a first rendition, in response to receiving a first transformation triggering event;
transforming the first content item by at least partially using the first rendition from a first format to a second format, in response to detecting a change to the first content item or a change to metadata associated with the first content item; and
applying two or more machine learning models to the transformation such that a second rendition of the first content item is generated and stored in one or more storage media devices;
wherein a first machine learning model generates an association between the first format and the second format;
the first machine learning transformation model invokes a transformation policy based on the association; and
the transformation policy is invoked to update the first content item or changes in the association.
18 . The computer program product of claim 17 , wherein the second rendition of the first content item is stored without re-invoking the first transformation triggering event.
19 . The computer program product of claim 17 , further comprising:
invoking an action to perform based upon the first rendition in order to perform an additional task.
20 . The computer program product of claim 19 , wherein the additional task is adding metadata or moving the first content item to a new location based upon information contained therein.