RepositoryWebrefWebrefAnnotationStats

AI Overview😉

  • Potential purpose of module: This module appears to be responsible for analyzing and extracting statistical information from annotations within a document. Annotations can include entities, concepts, and mentions, which are used to provide context and meaning to the content. The module's purpose is to provide a deeper understanding of the document's structure and content, which can be used to improve search results and relevance.
  • Impact on search results: The extracted statistics can be used to fine-tune internal scoring functions, such as document-length normalization, which can impact the ranking of search results. By analyzing the annotations and their context, the module can help identify more relevant and accurate results, improving the overall search experience. This can lead to more accurate and relevant search results, especially for complex queries or those that rely on entity-based searches.
  • Optimization strategies for websites: To be more favorable for this function, websites can focus on creating high-quality, structured content with clear annotations and entity markings. This can include using schema.org markup, providing accurate and consistent entity information, and ensuring that content is well-organized and easily parseable. Additionally, websites can focus on creating content that is rich in context and meaning, with clear relationships between entities and concepts, which can help the module better understand the content and provide more accurate search results.

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

Detailed statistics about the annotations in the document. Contains, for example, the number of ranges with name matches, the number of entities matched, and the number of entities with mentions. This information can be used to tune some WebRef-internal scoring functions based on existing annotations (e.g., document-length normalization in global link support). Next available tag: 10.

Attributes

  • docWeight (type: number(), default: nil) - The relative weight of the document, used when aggregating information from multiple documents.
  • ngramContext (type: list(GoogleApi.ContentWarehouse.V1.Model.RepositoryWebrefNgramContext.t), default: nil) - Extracted n-grams context scores (in cdoc language, weighted by doc_weight) output if webref_populate_annotation_ngrams is enabled.
  • numCandidates (type: String.t, default: nil) - The total number of candidates.
  • numConceptsWithCandidates (type: String.t, default: nil) - The total number of concepts with at least 1 candidate.
  • numConceptsWithMentions (type: String.t, default: nil) - The total number of concepts with at least 1 mention.
  • numRangesWithCandidates (type: String.t, default: nil) - The total number of RangeData objects with at least one candidate.
  • statsPerType (type: list(GoogleApi.ContentWarehouse.V1.Model.RepositoryWebrefAnnotationStatsPerType.t), default: nil) - Statistics for each token type.

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.RepositoryWebrefWebrefAnnotationStats{
    docWeight: number() | nil,
    ngramContext:
      [GoogleApi.ContentWarehouse.V1.Model.RepositoryWebrefNgramContext.t()]
      | nil,
    numCandidates: String.t() | nil,
    numConceptsWithCandidates: String.t() | nil,
    numConceptsWithMentions: String.t() | nil,
    numRangesWithCandidates: String.t() | nil,
    statsPerType:
      [
        GoogleApi.ContentWarehouse.V1.Model.RepositoryWebrefAnnotationStatsPerType.t()
      ]
      | nil
  }

Functions

Link to this function

decode(value, options)

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

Unwrap a decoded JSON object into its complex fields.