CrowdingPerDocData

AI Overview😉

  • The potential purpose of this module is to analyze and group similar news articles together, likely to prevent overcrowding of search results with duplicate or very similar content. This is known as "crowding" in search engine optimization (SEO) terminology.
  • This module could impact search results by reducing the visibility of duplicate or very similar news articles, allowing for a more diverse range of search results. This could lead to a better user experience, as users are shown a wider range of relevant content rather than multiple versions of the same story.
  • To be more favorable to this function, a website could ensure that their news articles are unique and provide distinct value to users. This could be achieved by providing original reporting, unique insights, or different perspectives on a story. Additionally, websites could focus on creating high-quality, in-depth content that stands out from other similar articles, making it more likely to be shown in search results.

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

Attributes

  • newscluster (type: list(GoogleApi.ContentWarehouse.V1.Model.CrowdingPerDocDataNewsCluster.t), default: nil) -

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.CrowdingPerDocData{
  newscluster:
    [GoogleApi.ContentWarehouse.V1.Model.CrowdingPerDocDataNewsCluster.t()]
    | nil
}

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.