QualitySalientTermsDocData

AI Overview😉

  • The potential purpose of this module is to analyze and understand the content of a webpage by identifying the most important keywords and phrases (salient terms) and their frequency, as well as the language and quality of the content. This helps Google to better comprehend the topic and relevance of the page.
  • This module could impact search results by influencing the ranking of a webpage based on the quality and relevance of its content. Webpages with high-quality, relevant, and well-structured content may be ranked higher, while those with low-quality or irrelevant content may be ranked lower. The module's analysis of salient terms and language may also help Google to better match search queries with relevant webpages.
  • To be more favorable for this function, a website may:
    • Use high-quality, engaging, and relevant content that clearly communicates the topic and purpose of the page.
    • Optimize content structure and formatting to make it easy for users and search engines to understand.
    • Use keywords and phrases strategically, but naturally, to help search engines understand the content's relevance and topic.
    • Ensure that the language and tone of the content are appropriate for the target audience and topic.
    • Provide a clear and concise title, description, and headings that accurately summarize the content.

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

DocData contains additional salient-term-set-level information that complements a SalientTermSet.

Attributes

  • confidence (type: number(), default: nil) - confidence is a measurement of how much data we had to compute the SalientTermSet. Range: [0.0, 1.0]
  • headVolumeRatio (type: number(), default: nil) - head_volume_ratio is the ratio of the sum of term frequency of the top K terms over the volume of all terms. Range: [0.0, 1.0]. K is defined by Accumulator2Params::head_size.
  • language (type: String.t, default: nil) - language is the main language of this SalientTermSet.
  • signalData (type: list(GoogleApi.ContentWarehouse.V1.Model.QualitySalientTermsSignalData.t), default: nil) - signal_data contains signal-specific (e.g., body, anchors, clicks) data for this SalientTermSet.
  • virtualVolume (type: number(), default: nil) - virtual_volume is a measurement of how much data we had to compute the SalientTermSet. Range: [0.0, +infinity)].

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.QualitySalientTermsDocData{
  confidence: number() | nil,
  headVolumeRatio: number() | nil,
  language: String.t() | nil,
  signalData:
    [GoogleApi.ContentWarehouse.V1.Model.QualitySalientTermsSignalData.t()]
    | nil,
  virtualVolume: number() | nil
}

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.