ReneEmbeddingCluster

AI Overview😉

  • The potential purpose of this module is to group similar content embeddings into clusters, allowing Google to better understand the relationships between different pieces of content. This can help improve search results by identifying patterns and connections between content that may not be immediately apparent.
  • This module could impact search results by influencing the ranking of content that is closely related to other content in the same cluster. For example, if a user searches for a specific topic, the search results may prioritize content that is part of a cluster with similar content, even if it's not an exact match. This could lead to more relevant and diverse search results.
  • To be more favorable for this function, a website could focus on creating high-quality, relevant, and diverse content that is closely related to other content on the site. This could include using natural language processing techniques to identify and create content that is semantically similar to other content on the site. Additionally, using structured data and schema markup to provide Google with additional context about the content could help improve its chances of being clustered with similar content.

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

Message to represent a cluster of the embedding space.

Attributes

  • id (type: integer(), default: nil) - Id of the cluster.
  • squaredDistance (type: number(), default: nil) - Squared distance of the current embedding to the cluster center.

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.ReneEmbeddingCluster{
  id: integer() | nil,
  squaredDistance: number() | nil
}

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.