ResearchScamNearestNeighborsNeighbor

Research SCAMSearch Infrastructure

GoogleApi.ContentWarehouse.V1.Model.ResearchScamNearestNeighborsNeighbor

out of 10

Low

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

Sort:|Filter:

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.