System and method for adaptive ranking of plurality of video segments

A computer system comprising:

• one or more processors;
• and
• a memory coupled to the one or more processors, the memory for storing instructions which, when executed by the one or more processors, cause the one or more processors to perform a method for adaptive ranking of a plurality of video segments in real time, the method comprising:
• receiving, at an adaptive ranking system, a multimedia content, wherein the multimedia content is received from one or more input devices in real-time, wherein the multimedia content is divided to create the plurality of video segments in real-time, wherein the plurality of video segments is created based on one or more parameters;
• displaying, at the adaptive ranking system, the plurality of video segments on one or more social media platforms, wherein the plurality of video segments is displayed on the one or more social media platforms in real time;
• ranking, at the adaptive ranking system, the plurality of video segments displayed on the one or more social media platforms, wherein ranking of the plurality of video segments is based on a performance data of each of the plurality of video segments over the one or more social media platforms, wherein the plurality of video segments is ranked for targeting the plurality of users based on one or more factors, wherein video segments of the plurality of video segments that exceeds a predefined threshold are a first group of video segments;
• extracting, at the adaptive ranking system, one or more attributes associated with the first group of video segments in real-time, wherein the one or more attributes are extracted by performing audio excitement analysis of the first group of video segments;
• and
• clustering, at the adaptive ranking system, the first group of video segments in real-time, wherein the clustering of the first group of video segments is done based on the one or more attributes and audio excitement analysis to optimize the adaptive ranking system, wherein the first group of video segments are clustered using machine learning algorithms.

A non-transitory computer-readable storage medium encoding computer executable instructions that, when executed by at least one processor, performs a method for adaptive ranking of a plurality of video segments in real time, the method comprising:

• receiving, at a computing device, a multimedia content, wherein the multimedia content is received from one or more input devices in real-time, wherein the multimedia content is divided to create the plurality of video segments in real-time, wherein the plurality of video segments is created based on one or more parameters;
• displaying, at the computing device, the plurality of video segments on one or more social media platforms, wherein the plurality of video segments is displayed on the one or more social media platforms in real time;
• ranking, at the computing device, the plurality of video segments displayed on the one or more social media platforms, wherein ranking of the plurality of video segments is based on a performance data of each of the plurality of video segments over the one or more social media platforms, wherein the plurality of video segments is ranked for targeting the plurality of users based on one or more factors, wherein video segments of the plurality of video segments that exceeds a predefined threshold are a first group of video segments;
• extracting, at the computing device, one or more attributes associated with the first group of video segments in real-time, wherein the one or more attributes are extracted by performing audio excitement analysis of the first group of video segments;
• and
• clustering, at the computing device, the first group of video segments in real-time, wherein the clustering of the first group of video segments is done based on the one or more attributes and audio excitement analysis to optimize the adaptive ranking system, wherein the first group of video segments are clustered using machine learning algorithms.