Document Vector Hashing

Manipulator

This node creates a document vector for each document representing it in the terms space. The values of the feature vectors can be specified as boolean values or as values of either the relative frequency or the absolute frequency of the terms. The advantages of using this node instead of the normal document vector node is that the dimension of the vectors is always fixed and therefore this node is streamable.

Input Ports

  1. Type: Data
    The input table containing the documents.

Output Ports

  1. Type: Data
    An output table containing the input documents with the corresponding document vectors.
  2. Type: VectorHashingPortObject
    The model output containing the specifications that have been used for document vector creation.

  1. Streaming Sentiment Analysis of Documents using Document Vector Hashing

    This workflow demonstrates how to use the Document Vector Hashing node to execute the Sentiment Analysis example in a st…
    Users > knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing

Extension

This node is part of the extension

KNIME Textprocessing

 v4.0.0

Short Link

Drag node into KNIME Analytics Platform