Hierarchical video concept tagging and indexing system for learning content orchestration

A computer system for automatically generating a hierarchy of concepts described in a video using semantic concept matching, the computer system comprising:

• a processor, a computer-readable memory, a computer-readable tangible storage device, and program instructions stored on at least one or more storage devices for execution by at least one or more processors via at least one or more memories, wherein the computer system is configured to:
• obtain a video segment having a distinct running time, and including information related to one or more topics based on at least one of (i) closed captioning data, (ii) spoken language in the video, and (iii) visual content in the video;
• upon determining that there is closed captioning data, parse the information of the video segment into discrete information based on the closed captioning data;
• upon determining that there is no closed captioning data:
• parse the information of the video segment based on at least one of (i) the spoken language in the video, which is converted to text by the computer, and (ii) visual content in the video, which is recognized by the computer;
• and
• upon determining that there is no visual content in the video, obtain one or more topic tags of the video segment;
• relate the discrete information to a predetermined relevant topic;
• determine one or more attributes for weighting each of the discrete information related to the predetermined relevant topic within the video segment;
• create a hierarchy of concepts of the video segment based upon, at least, the weighting of each of the discrete information related to the predetermined relevant topic within the running time of the video segment based upon the presence of the one or more attributes;
• filter out topics that occur less than a predetermined number of times within the video segment;
• create a weighted graph, wherein each concept of the hierarchy of concepts is a weighted node within the graph;
• and
• store the weighted graph for the video segment in a searchable database to provide a granular search tool of the video.

A computer program product stored on a non-transitory computer readable medium having computer readable program code embodied thereon that is executable by a computer for automatically generating a hierarchy of concepts described in a video using semantic concept matching, the computer program product comprising computer readable program code that when executed configures a computer to perform the acts of:

• obtaining a video segment having a distinct running time, and including information related to one or more topics based on at least one of (i) closed captioning data, (ii) spoken language in the video, and (iii) visual content in the video;
• upon determining that there is closed captioning data, parsing the information of the video segment into discrete information based on the closed captioning data;
• upon determining that there is no closed captioning data:
• parsing the information of the video segment based on at least one of (i) the spoken language in the video, which is converted to text by the computer, and (ii) the visual content in the video, which is recognized by the computer;
• and
• upon determining that there is no visual content in the video, obtaining one or more topic tags of the video segment;
• relating the discrete information to a predetermined relevant topic;
• determining one or more attributes for weighting each of the discrete information related to the predetermined relevant topic within the video segment;
• creating a hierarchy of concepts of the video segment based upon, at least, the weighting of each of the discrete information related to the predetermined relevant topic within the video segment based upon the presence of the one or more attributes;
• filtering out topics that occur less than a predetermined number of times within the video segment;
• creating a weighted graph, wherein each concept of the hierarchy of concepts is a weighted node within the graph;
• and
• storing the weighted graph for the video segment in a searchable database to provide a granular search tool of the video.