VideoContentSearchQnaAnchorSetFeatures

AI Overview😉

  • The potential purpose of this module is to help Google's search algorithm understand and rank video content based on its relevance to a user's query, particularly in the context of question-answer pairs. It appears to be focused on identifying and scoring video segments that provide accurate and relevant answers to user questions.
  • This module could impact search results by influencing the ranking of video content, potentially promoting videos that provide clear and concise answers to user questions. It may also affect the way Google's algorithm clusters and groups related questions and answers, which could impact the diversity and relevance of search results.
  • A website may change things to be more favorable for this function by optimizing their video content to provide clear and concise answers to user questions, using relevant keywords and phrases, and structuring their content in a way that makes it easy for Google's algorithm to identify and score. Additionally, websites may benefit from using schema markup and other forms of structured data to help Google understand the content and context of their videos.

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

Debug info for Q&A anchors. Next ID: 15

Attributes

  • backgroundEncodingPath (type: String.t, default: nil) - Path to Descartes background encoding in the form of a serialized drishti.DenseFeatureData proto. This is generated by the flume_generate_background_encoding binary.
  • descartesModelVersion (type: String.t, default: nil) - This field is used for debugging which model the decartes_model_score is generated from. You can learn more about the Descartes model at go/descartes-qa.
  • descartesScoreThreshold (type: number(), default: nil) - Descartes score threshold for determining whether to output a QA pair as an anchor. This currently effects only the Descartes ranking score.
  • dolphinConfig (type: GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchDolphinScoringConfig.t, default: nil) - The configuration used for fetching Dolphin scores.
  • ensembleModelPath (type: String.t, default: nil) - Path to Ranklab ensemble model used in post-trigger step.
  • ensembleModelScoreThreshold (type: number(), default: nil) - Minimum score for video anchor to pass the post-trigger step. Calculated by training a logisitic regression model with 95% precision. Training colab can be found at go/video-qa-ensemble.
  • minEntityTopicalityScore (type: number(), default: nil) - Threshold for determining whether to consider an entity from a CDoc for sourcing questions on that topic. Learn more about this score at: http://go/topicality-score
  • minQuestionDistance (type: number(), default: nil) - Threshold for determining whether questions belong in the same cluster.
  • relatedQuestionsSstablePath (type: String.t, default: nil) - Path to the Related Questions SSTable that maps entities to questions.
  • spanDurationSecs (type: String.t, default: nil) - The duration threshold for merging captions.

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.VideoContentSearchQnaAnchorSetFeatures{
    backgroundEncodingPath: String.t() | nil,
    descartesModelVersion: String.t() | nil,
    descartesScoreThreshold: number() | nil,
    dolphinConfig:
      GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchDolphinScoringConfig.t()
      | nil,
    ensembleModelPath: String.t() | nil,
    ensembleModelScoreThreshold: number() | nil,
    minEntityTopicalityScore: number() | nil,
    minQuestionDistance: number() | nil,
    relatedQuestionsSstablePath: String.t() | nil,
    spanDurationSecs: 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.