VideoContentSearchGenerativeTopicPredictionFeatures

AI Overview😉

  • The potential purpose of this module is to analyze and predict the topics of video content in search results. It appears to use a generative model to predict topics and returns a list of possible topics, along with the model name and any available ground truth topics from training data.
  • This module could impact search results by allowing Google to better understand the content of videos and return more relevant results for users searching for specific topics. It may also help to improve the clustering of related videos in search results. The use of beam search with a beam size greater than 1 suggests that the model is designed to generate multiple possible topics, which could lead to a more diverse set of search results.
  • To be more favorable for this function, a website could focus on creating high-quality, topic-specific video content with clear and descriptive titles, descriptions, and tags. This could help the model to better understand the topic of the video and return more accurate predictions. Additionally, using schema markup to provide additional context about the video content could also be beneficial. Furthermore, creating a clear and consistent information architecture on the website could also help the model to better understand the relationships between different pieces of content and improve the accuracy of topic predictions.

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GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchGenerativeTopicPredictionFeatures (google_api_content_warehouse v0.4.0)

The inference result features coming from the prediction service that generates the topics.

Attributes

  • groundTruthTopic (type: String.t, default: nil) - This field is present if we already have a ground truth topic from the training data.
  • modelName (type: String.t, default: nil) - The name of the model where the predictions come from.
  • predictions (type: list(String.t), default: nil) - Inference results from the prediction service. Since we generally use beam search with beam_size > 1, this field is repeated to capture all the generated topic beams.

Summary

Types

t()

Functions

decode(value, options)

Unwrap a decoded JSON object into its complex fields.

Types

Link to this type

t()

@type t() ::
  %GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchGenerativeTopicPredictionFeatures{
    groundTruthTopic: String.t() | nil,
    modelName: String.t() | nil,
    predictions: [String.t()] | nil
  }

Functions

Link to this function

decode(value, options)

@spec decode(struct(), keyword()) :: struct()

Unwrap a decoded JSON object into its complex fields.