Symbolic Hyperdimensional Vector

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A Symbolic Hyperdimensional Vector is very-wide vector data item that represents an information unit.

  • Context:
    • It can (typically) be an Integer Vector.
    • It can (typically contain thousands of numbers.
    • It can (typically) be a fundamental element in Hyperdimensional Computing where information is represented using high-dimensional vectors.
    • It can be manipulated using algebraic operations to perform tasks such as pattern recognition, natural language processing, and data mining.
    • It can allow for the encoding of complex structures and relationships in a computationally efficient manner.
    • It can be a form of Analog Representation in computational models.
    • It can be joined with other hyperdimensional vectors to form composite representations.
  • Example(s):
    • Representing words in a natural language processing task as hyperdimensional vectors, where each dimension could represent semantic or syntactic properties.
    • Encoding images as hyperdimensional vectors in a pattern recognition system, where each dimension represents different features or properties of the image.
    • Using hyperdimensional vectors in a robotic mapping system to represent the spatial environment in which the robot operates.
  • Counter-Example(s):
    • Using simple numerical vectors with a low number of dimensions for data representation.
    • Representing data in a relational database as records and fields instead of hyperdimensional vectors.
  • See: Hyperdimensional Computing, High-Dimensional Data, Vector (Mathematics and Physics), Analog Computing, Pattern Recognition, Natural Language Processing, Data Mining.


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