System for content delivery estimation
A system for processing video files includes receiving the video files, transcoding each of the video files, and making available each of the transcoded video files to a target platform. A predictive analysis process estimates the respective end times that each of the video files will be available for the target platform. Each of the respective end times are compared against a licensing window associated with the respective video file.
1. A method for processing each of a plurality of video files within a video content management system having a processor that performs a plurality of sequential processes that together receive, transcode, and make available each of the video files to a target platform, each process associated with a respectively different queue, the processor configured to:
(a) estimate, using a predictive analysis process, respective end times that each of said video files will be said available for said target platform;
(b) comparing each of said respective end times to a start of a respective licensing window associated with said respective video file for said target platform;
(c) based on the comparison, generate an alert indicating that a late video file has an associated end time following the start of its respective licensing window; and
(d) receive and implement an instruction that rearranges at least some of the plurality of video files in their respective queues in a manner that the late video file no longer has an associated end time following the start of its respective licensing window.
2. The method of claim 1 wherein said plurality of video files are provided by a plurality of different content providers.
3. The method of claim 2 wherein each of said video files are provided as a respective package that includes a respective metadata file.
4. The method of claim 1 wherein said processing further includes configuring one of said video files for a transactional video on demand system where said one of said video files may be purchased separate from other video files.
5. The method of claim 4 wherein said estimating is further based upon whether said one of said video files is for said transactional video on demand system.
6. The method of claim 1 wherein each of said video files includes a respective metadata file, and wherein said metadata file indicates a start time and a start date for said respective video file.
7. The method of claim 6 wherein each of said video files includes said respective metadata file, and wherein said metadata file indicates an end time and an end date for said respective video file.
8. The method of claim 7 wherein said start time, said start date, said end time, and said end date collectively correspond to said respective licensing window.
9. The method of claim 1 wherein said processing further includes a discovery process that analyzes characteristics of each of said video files and said estimating is further based upon said discovery process.
10. The method of claim 9 wherein said analyzes characteristics of each of said video files by said discovery process is based upon a corresponding metadata file.
11. The method of claim 1 wherein said processing further includes a disclaimer stitching process that modifies each of said video files by including a disclaimer and said estimating is further based upon said disclaimer stitching process.
12. The method of claim 1 wherein said processing further includes a quality check process that verifies the quality of each of said video files and said estimating is further based upon said quality check process.
13. The method of claim 1 wherein said processing further includes an encryption process that encrypts each of said video files and said estimating is further based upon said encryption process.
14. The method of claim 1 wherein said processing further includes a measure of a queue of said processing and said estimating is further based upon said queue.
15. The method of claim 1 wherein said comparing is based upon a machine learning process.
16. The method of claim 15 wherein said machine learning process is based upon a random forest algorithm.
17. The method of claim 1 wherein said comparing is based upon current processing capabilities of said video content management system.
18. The method of claim 1 wherein said comparing is based upon a plurality of video files to be processed by said video content management system.