ResearchScamNearestNeighbors
Research SCAMSearch InfrastructureGoogleApi.ContentWarehouse.V1.Model.ResearchScamNearestNeighbors
SEO Analysis
AI GeneratedCore search serving infrastructure. While not a direct ranking signal, these systems process and serve search results. This model (Research Scam Nearest Neighbors) contains 6 attributes that define its data structure. Key functionality includes: Data point for which we computed nearest neighbors. This field is set based on the data_id_str field in the QueryRequest GFV (or SSTable key if data_i...
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
6docidstringnilFull type: String.tData point for which we computed nearest neighbors. This field is set based on the data_id_str field in the QueryRequest GFV (or SSTable key if data_id_str is not present), and thus can be arbitrary data, e.g. docid, URL, query string.
metadatastringnilFull type: String.tMetadata about the query. This field is populated if and only if: 1) ScaM is running in offline query-database or online mode and; 2) The metadata is directly fetched from the userinfo field inside GFV and; 3) MetadataConfig.userinfo.set_user_info_for_query is set to true. The field name is kept as "metadata" for consistency with neighbors.
nilFull type: list(GoogleApi.ContentWarehouse.V1.Model.ResearchScamNearestNeighborsNeighbor.tAll its neighbors.
neighborSelectionOverrideResearchScamNeighborSelectionOverride →nilFull type: GoogleApi.ContentWarehouse.V1.Model.ResearchScamNeighborSelectionOverride.tPropagate neighbor selection override information during offline search.
nilFull type: GoogleApi.ContentWarehouse.V1.Model.ResearchScamGenericFeatureVector.tThe query vector for which we computed nearest neighbors.
retrievedVersionstringnilFull type: String.tThe version ID of the server that responded to this query, if one was specified. This field is not populated for offline (i.e. Flume rather than RPC) search.