QualitySalientTermsSignalData

AI Overview😉

  • The potential purpose of this module is to analyze and weight the importance of specific terms or keywords within a document or webpage. It appears to be a part of Google's Quality algorithm, which aims to evaluate the relevance and usefulness of content to users. This module, specifically, focuses on identifying "salient terms" that are most representative of the content and calculating their significance.
  • This module could impact search results by influencing the ranking of webpages based on the relevance and importance of specific keywords. If a webpage contains high-quality, salient terms that align with the user's search query, it may be boosted in the search rankings. Conversely, if a webpage lacks relevant keywords or contains low-quality content, it may be demoted in the rankings.
  • A website may change things to be more favorable for this function by ensuring that their content is high-quality, informative, and rich in relevant keywords. This could involve:
    • Conducting thorough keyword research to identify the most salient terms related to their content.
    • Creating high-quality, engaging, and informative content that incorporates these keywords naturally.
    • Optimizing meta tags, titles, and descriptions to include relevant keywords.
    • Using header tags and subheadings to structure content and highlight important keywords.
    • Regularly updating and refining content to ensure it remains relevant and useful to users.

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

SignalData stores signal-specific salient-term-set-level information. Stores mostly internal data as it is one of the primary data structures used in the populators.

Attributes

  • bias (type: number(), default: nil) - A fixed bias for this signal, the higher the stronger. This can be used to balance the weight of signals independently of the confidence we give it. This field is only available in debug mode.
  • confidence (type: number(), default: nil) - The measurement of how much we trust this signal. Range: [0.0, 1.0] This field is available is both debug and non-debug mode.
  • halfSalience (type: number(), default: nil) - Raw saliences equal to half_salience will be equal to 0.5 normalized. Range: [0, volume]. This field is only available in debug mode.
  • noiseCorrection (type: number(), default: nil) - The minimum TF for a term not to be considered noise. While the possible range of values for this field is [0, observed_volume], it is expected to be a somewhat small percentage of observed_volume (e.g. 5%). This field is only available in debug mode.
  • observedConfidence (type: number(), default: nil) - The measurement of how much we trust this signal, calculated using the observed volume. Range: [0.0, 1.0] This field is only available in debug mode.
  • observedVolume (type: number(), default: nil) - The amount of signal we observed for a document. Range: [0.0, +infinity) This field is only available in debug mode.
  • rawVolume (type: number(), default: nil) - The amount of raw signal we observed for a document. Range: [0.0, +infinity) This field is only available in debug mode.
  • source (type: String.t, default: nil) - source is the type of the signal of this SignalData.
  • volume (type: number(), default: nil) - The amount of signal left after applying all corrections. Range: [0.0, +infinity) This field is only available in debug mode.

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.QualitySalientTermsSignalData{
  bias: number() | nil,
  confidence: number() | nil,
  halfSalience: number() | nil,
  noiseCorrection: number() | nil,
  observedConfidence: number() | nil,
  observedVolume: number() | nil,
  rawVolume: number() | nil,
  source: String.t() | nil,
  volume: number() | nil
}

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.