RepositoryWebrefCategoryAnnotationHitCatSource

AI Overview😉

  • Potential purpose of module in simple language: This module, called HitCat, appears to be a page classifier that assigns categories to web pages with a confidence score. It helps Google understand the relevance of a page to a particular topic or category.
  • How it could impact search results: The HitCat module could impact search results by influencing the ranking of pages based on their relevance to a search query. Pages with high confidence scores for a particular category may be considered more relevant and therefore rank higher in search results. This could lead to more accurate and targeted search results, but also potentially exclude pages that are less confident in their categorization.
  • How a website may change things to be more favorable for this function: To be more favorable for the HitCat module, a website may want to:
    • Clearly define and structure its content to facilitate categorization
    • Use relevant and consistent keywords and metadata to help Google understand the page's topic
    • Ensure that the page's content is high-quality and relevant to the assigned category

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

The HitCat page classifier. See go/hitcat2 If you use any HitCat score, please: 1. Add your use-case to go/hits-clients. 2. Subscribe to hits-users@ to receive general updates.

Attributes

  • confidence (type: number(), default: nil) - Confidence of the category in the range [0.0, 1.0). If a page has the category "NBA" with high confidence we also expect it to have the "Basketball" with high confidence. Categories with a confidence lower than 0.05 are omitted. This can be interpreted as a confidence of 0, i.e. a strong signal that the category is not relevant for the page. For some categories this score is calibrated per-category to estimate the true precision. E.g., 70% of documents retrieved within the confidence range [0.7 - eps, 0.7 + eps] will be relevant when eps is close to 0.
  • cumulativeConfidence (type: number(), default: nil) - Calibrated cumulative confidence guaranteeing maxmial recall for a precision target. E.g., At least 90% of documents retrieved with cumulative_confidence >= 0.9 will be relevant. This score is always calibrated per-category to estimate the true cumulative precision and is not set for uncalibrated categories.
  • experimentalConfidence (type: number(), default: nil) - Note: For testing the next version. May change at any time. Experimental confidence of the category in the range (0.0, 1.0).

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.RepositoryWebrefCategoryAnnotationHitCatSource{
    confidence: number() | nil,
    cumulativeConfidence: number() | nil,
    experimentalConfidence: number() | nil
  }

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.