Distributional Vector
(Redirected from co-occurrence vector)
A Distributional Vector is a vector that represents an item based on its context within a large dataset.
- Context:
- It can be seen as a numerical representation of a word or item that reflects its contextual usage.
- It can be generated based on the frequency or co-occurrence of words/items in proximity to the target word/item in a given corpus or dataset.
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- Example(s):
- Word2Vec Vector.
- TF-IDF Vector (Term Frequency-Inverse Document Frequency) vectors in document retrieval.
- Topic Modeling Vector generated from the distribution of topics across documents.
- Customer Segmentation Vector that represent customer behavior based on purchase history.
- Genomic Vectors representing the context of a particular gene within a genome.
- Embedding Space Vector.
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- Counter-Example(s):
- One-hot Vectors: These vectors represent a word or item without any contextual information.
- See: Embedding Space, Co-Occurrence Word Vector, Distributional Model, Distributional Continuous Word Vector.