Generating tags for a digital video

A system comprising:

• memory comprising a neural network and a set of tagged feature vectors corresponding to a set of media content items, the set of tagged feature vectors comprising feature vectors generated from particular media content items and tagged with labels that correspond to the particular media content items;
• at least one processor;
• and
• at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
• extract a set of frames from a video;
• generate, utilizing the neural network, feature vectors for the set of frames;
• and
• generate a set of tags to associate with the video by:
• determining distance values between the feature vectors for the set of frames and one or more tagged feature vectors from the set of tagged feature vectors;
• selecting tags from the one or more tagged feature vectors from the set of tagged feature vectors based on the determined distance values;
• and
• aggregating the tags selected from the one or more tagged feature vectors.

A computer-implemented method for automatic tagging of videos, the computer-implemented method comprising:

• extracting a set of frames from a video;
• generating, utilizing a neural network, feature vectors for the set of frames;
• performing a step for generating an aggregated feature vector from the feature vectors;
• determining one or more tagged feature vectors similar to the aggregated feature vector based on distances between the aggregated feature vector and the one or more tagged feature vectors, wherein the one or more tagged feature vectors are associated with an identified set of tagged feature vectors corresponding to a set of media content items and comprising feature vectors generated from particular media content items and tagged with labels that correspond to the particular media content items;
• and
• generating a set of tags to associate with the video by:
• selecting tags from the one or more tagged feature vectors based on the distances between the aggregated feature vector and the one or more tagged feature vectors;
• and
• aggregating the tags selected from the one or more tagged feature vectors.