ReneEmbeddingClusterList

AI Overview😉

  • The potential purpose of this module is to group similar content or entities together based on their semantic meaning, represented as clusters of embeddings. This allows Google to better understand the relationships between different pieces of content and provide more accurate search results.
  • This module could impact search results by influencing the ranking of pages that are part of a cluster, potentially promoting more relevant or authoritative content within a topic or entity. It may also help to reduce duplication or redundancy in search results by grouping similar content together.
  • To be more favorable for this function, a website could focus on creating high-quality, semantically rich content that is closely related to a specific topic or entity. This could involve using natural language processing techniques to identify relevant keywords and phrases, as well as creating structured data and metadata that helps search engines understand the relationships between different pieces of content.

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

Message to represent a list of clusters.

Attributes

  • clusters (type: list(GoogleApi.ContentWarehouse.V1.Model.ReneEmbeddingCluster.t), default: nil) - Clusters.

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.ReneEmbeddingClusterList{
  clusters: [GoogleApi.ContentWarehouse.V1.Model.ReneEmbeddingCluster.t()] | nil
}

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.