VideoContentSearchMultimodalTopicTrainingFeatures

VideoSearch Infrastructure

GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchMultimodalTopicTrainingFeatures

9
out of 10
Critical
SEO Impact
Multimodal features for a single generated topic used to build training data.

SEO Analysis

AI Generated

Related to video content processing and YouTube integration. Video content appears in universal search results, video carousels, and YouTube search. This model processes video signals that determine how video content is ranked and displayed in both web search and YouTube search results.

Actionable Insights for SEOs

  • Monitor for changes in rankings that may correlate with updates to this system
  • Consider how your content strategy aligns with what this signal evaluates

Attributes

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Default: nilFull type: GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchFrameSimilarityInterval.t

The similarity info for the frame with maximum similarity to the topic in its visual interval. The repeated similarity field in this proto has a single value corresponding to the maximum similarity. This similarity score is used to filter and pick the training data examples.

normalizedTopicstring
Default: nilFull type: String.t

The topic/query normalized for Navboost and QBST lookups as well as fetching of the Rankembed nearest neighbors.

Default: nilFull type: GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchQbstTermsOverlapFeatures.t

QBST terms overlap features for a candidate query.

Default: nilFull type: GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchRankEmbedNearestNeighborsFeatures.t

Rankembed similarity features for a candidate nearest neighbor rankembed query.

Default: nilFull type: GoogleApi.ContentWarehouse.V1.Model.VideoContentSearchSaftEntityInfo.t

The information about the saft entity annotation for this topic.

topicDenseVectorlist(number(
Default: nil

Raw float feature vector of the topic's co-text embedding representation in the Starburst space.