VideoContentSearchQnaAnchorFeatures

AI Overview😉

  • The potential purpose of this module is to analyze and rank video content based on its relevance to a user's question, taking into account various factors such as the similarity between the question and the video title, the content of the video, and the user's search history. This module appears to be a part of Google's video search algorithm, aimed at providing users with the most relevant and accurate video results for their queries.
  • This module could impact search results by influencing the ranking of video content. Videos that are deemed more relevant and accurate based on the factors analyzed by this module may be ranked higher in search results, while less relevant videos may be ranked lower. This could lead to a more personalized and accurate search experience for users, as they are more likely to find videos that closely match their search queries.
  • A website may change things to be more favorable for this function by optimizing their video content to better match user search queries. This could involve using more descriptive and accurate video titles, providing more detailed and relevant video descriptions, and ensuring that the video content itself is high-quality and relevant to the user's search query. Additionally, websites may want to focus on improving the overall user experience, such as by providing fast loading times, easy navigation, and a user-friendly interface, as these factors may also be taken into account by the algorithm.

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

Features for individual Q&A anchors. Next ID: 23

Attributes

  • answer (type: String.t, default: nil) - Segment of text from the ASR.
  • descartesDotScore (type: number(), default: nil) -
  • descartesRankingScore (type: number(), default: nil) -
  • dolphinModelType (type: String.t, default: nil) -
  • dolphinScore (type: number(), default: nil) - Dolphin score calculated using the question as the query, the ASR passage as the answer. See go/dolphin-models to learn more.
  • editDistance (type: number(), default: nil) - Edit distance of the question and the title from 0 to 1 where 1 is most similar.
  • endMs (type: String.t, default: nil) - End time in milliseconds relative to the beginning of the video.
  • ensembleScore (type: number(), default: nil) -
  • isDuplicateOfTitle (type: boolean(), default: nil) - True if question_title_similarity is less than 0.2.
  • neonScore (type: number(), default: nil) - Neon similarity of question and title.
  • pointwiseNormalizedGapScore (type: number(), default: nil) - Pointwise GAP normalized score. Score ranges from 0 to 1 and corresponds to GAP precision. See go/wa-cgap-to-pgap-migration to learn more.
  • qbstScore (type: number(), default: nil) - QBST similarity of question and title.
  • queryCount (type: number(), default: nil) - NavBoostFeature f_query_count for questions that are NavBoost queries.
  • queryDocCount (type: number(), default: nil) - NavBoostFeature f_query_doc_count for questions that are NavBoost queries.
  • question (type: String.t, default: nil) - Question from Related Questions SSTable or NavBoost.
  • questionTitleSimilarity (type: number(), default: nil) -
  • questionType (type: String.t, default: nil) -
  • startMs (type: String.t, default: nil) - Start time in milliseconds relative to the beginning of the video.
  • videoDurationMs (type: String.t, default: nil) - Duration of the video.
  • videoTitle (type: String.t, default: nil) - Video title.
  • webrefMid (type: String.t, default: nil) - Mid corresponding to the WebRef entity from the CDoc that was used to source the question.
  • webrefTopicalityScore (type: number(), default: nil) - The WebRef entity topicality score. Learn more about this score at: http://go/topicality-score

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.VideoContentSearchQnaAnchorFeatures{
  answer: String.t() | nil,
  descartesDotScore: number() | nil,
  descartesRankingScore: number() | nil,
  dolphinModelType: String.t() | nil,
  dolphinScore: number() | nil,
  editDistance: number() | nil,
  endMs: String.t() | nil,
  ensembleScore: number() | nil,
  isDuplicateOfTitle: boolean() | nil,
  neonScore: number() | nil,
  pointwiseNormalizedGapScore: number() | nil,
  qbstScore: number() | nil,
  queryCount: number() | nil,
  queryDocCount: number() | nil,
  question: String.t() | nil,
  questionTitleSimilarity: number() | nil,
  questionType: String.t() | nil,
  startMs: String.t() | nil,
  videoDurationMs: String.t() | nil,
  videoTitle: String.t() | nil,
  webrefMid: String.t() | nil,
  webrefTopicalityScore: number() | nil
}

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.