Bag-of-Words (BoW) Vector-Feature Creation Function

A Bag-of-Words (BoW) Vector-Feature Creation Function is a distributional vectorization function that maps a text item to a bag-of-words vector (based on a bag-of-words count function).

• AKA: BoW Mapping Model.
• Context:
  • It can range from (typically) being a Corpus-based Bag-of-Words Mapping to being a Manually Created Bag-of-Words Mapping.
  • It can range from being a Document-level BoW Function to being a Sentence-level BoW Function to being a Text Window-based BoW Function.
  • It can be created by a Bag-of-Words Mapping System.
  • It can be a member of a Word Vector Feature Space.
  • It can (in the abstract) define a Bag-of-Words Vector Space.
  • …
• Counter-Example(s):
  • a Word Classification Function.
• See: Text Item Vectorization Structure, Continuous Distribution Mapping, Document-Wise Co-Occurrence Statistic.

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