VideoContentSearchSimilarityMatchInfo

AI Overview😉

  • The potential purpose of this module is to analyze the similarity between the spoken content in a video and the text content from a web document, such as instructions or descriptions. It appears to be used to match video content with relevant text-based information.
  • This module could impact search results by influencing the ranking of videos that have matching text-based content. Videos with higher similarity scores may be considered more relevant and therefore ranked higher in search results. This could lead to a better user experience, as users are more likely to find videos that accurately match their search queries.
  • A website may change things to be more favorable for this function by ensuring that their video content is accurately transcribed and matched with relevant text-based information, such as instructions or descriptions. This could involve using high-quality automatic speech recognition (ASR) systems to generate accurate transcripts, and ensuring that the text-based content is well-structured and easily machine-readable. Additionally, websites may want to consider optimizing their video metadata, such as titles, descriptions, and tags, to better match the content of the video.

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

Attributes

  • instructionStartMs (type: integer(), default: nil) - The timestamp of when the first token in the token sequence is spoken in the video.
  • instructionText (type: String.t, default: nil) - The instruction step text coming from the web document. Currently only populated for best_description_and_instruction_anchors_match_info.
  • referenceText (type: String.t, default: nil) - The reference text used for matching against token_sequence (e.g. description anchor text or instruction step text).
  • referenceTextTimeMs (type: integer(), default: nil) - The timestamp of when the reference text is pointing in the video (e.g. this is the description anchor timestamp when reference_text is description anchor. For instruction step used as the reference, no timestamps exists and thus this field is not populated).
  • scoringMethodName (type: String.t, default: nil) - Similarity scorer name.
  • similarityScore (type: number(), default: nil) - The similarity score given by the scoring method specified by the message scoring_method_name.
  • stepIndex (type: integer(), default: nil) - The index of the step in HowToInstructions that this token_sequence corresponds to.
  • tokenSequence (type: String.t, default: nil) - The matched token sequence text in ASR.
  • tokenSequenceLength (type: integer(), default: nil) - The length of the tokens in the token sequence.
  • tokenStartPos (type: integer(), default: nil) - The token offset of the matched token sequence from the beginning of the document.

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.VideoContentSearchSimilarityMatchInfo{
    instructionStartMs: integer() | nil,
    instructionText: String.t() | nil,
    referenceText: String.t() | nil,
    referenceTextTimeMs: integer() | nil,
    scoringMethodName: String.t() | nil,
    similarityScore: number() | nil,
    stepIndex: integer() | nil,
    tokenSequence: String.t() | nil,
    tokenSequenceLength: integer() | nil,
    tokenStartPos: integer() | nil
  }

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.