ResearchScamNearestNeighborsNeighbor

Research SCAMSearch Infrastructure

GoogleApi.ContentWarehouse.V1.Model.ResearchScamNearestNeighborsNeighbor

3
out of 10
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SEO Impact
Unwrap a decoded JSON object into its complex fields.

SEO Analysis

AI Generated

Core search serving infrastructure. While not a direct ranking signal, these systems process and serve search results. This model (Research Scam Nearest Neighbors Neighbor) contains 5 attributes that define its data structure. Key functionality includes: If crowding is enabled, the crowding attribute of this neighbor will be stored here.

Actionable Insights for SEOs

  • Understanding this model helps SEOs grasp Google's internal data architecture
  • Consider how this system might interact with other ranking signals

Attributes

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crowdingAttributestring
Default: nilFull type: String.t

If crowding is enabled, the crowding attribute of this neighbor will be stored here.

distancefloat(
Default: nil

This could be exact or approximate distance.

docidstring
Default: nilFull type: String.t

Neighbor data point. This field is set based on the data_id_str field in the GFV of the data point in the database (or SSTable key if data_id_str is not present), and thus can be arbitrary data, e.g. docid, URL, query string.

gfvResearchScamGenericFeatureVector →
Default: nilFull type: GoogleApi.ContentWarehouse.V1.Model.ResearchScamGenericFeatureVector.t

The field isn't populated by default, but when enabled (eg, in the ground-truth pipeline), this field provides the original database GFV corresponding to this result.

metadatastring
Default: nilFull type: String.t

Metadata about the neighbor. This is returned under some configurations as a serialized proto. The specific proto depends on which metadata is configured to be returned.