Hub
NodeNode / Manipulator

Strings To Document

Other Data Types Text Processing Transformation Streamable
Drag & drop
Like
Copy short link

Converts the specified strings to documents. For each row a document will be created and attached to that row. The strings of the specified columns will be used as title, authors, and full text. Furthermore the defined category, source, type, and date will be set.

Node details

Input ports
  1. Type: Table
    String input table
    An input data table containing string cells.ht
Output ports
  1. Type: Table
    String and document output table
    An output table containing the strings of the data of the input table as well as the created documents in an additional column.

Extension

The Strings To Document node is part of this extension:

Related workflows & nodes

  1. 03 Tagging
    Text mining Text processing POS
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    knime > Education > Self-Paced Courses > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    knime
  2. 03 Tagging
    Text mining Text processing Tag
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    tqthanh168 > Public > Self-Paced Courses > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    tqthanh168
  3. 03 Tagging
    Text mining Text processing Tag
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    oriensraymi > Public > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    oriensraymi
  4. 03 Tagging
    Text mining Text processing Tag
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    oriensraymi > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    oriensraymi
  5. 03 Tagging
    Text mining Text processing POS
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    bashir82 > Public > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    bashir82
  6. 03 Tagging
    Text mining Text processing POS
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    halverdog > Public > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    halverdog
  7. 03 Tagging
    Text mining Text processing POS
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    manuel1972 > Public > Self-Paced Courses > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    manuel1972
  8. 03 Tagging
    Text mining Text processing POS
    +4
    L4-TP SELF-PACED COURSE exercise. Apply parts-of-speech, named entity, and wildcard taggi…
    enekogonzalezme > Public > L4-TP Introduction to Text Processing > Exercises > 03 Tagging
    enekogonzalezme
  9. Lab 5 - 02 - Reading Text Data
    the32bitphoenix > Public > Lab 5 - Additional Examples > Lab 5 - 02 - Reading Text Data
    the32bitphoenix
  10. 01_From_Strings_to_Documents
    Books Text Mining From Words To Wisdom
    This workflow shows how to convert string-type columns into document-type columns. A docu…
    vincenzo > Public > From_Words_To_Wisdom_Book > Chapter2 > 01_From_Strings_to_Documents
    vincenzo