NodeDocument Vector

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 a specified column i.e. an tf*idf column. The dimension of the vectors will be the number of distinct terms in the BoW.

Input ports

  1. Documents input table Type: Data
    The input table containing the bag of words.

Output ports

  1. Documents output table Type: Data
    An output table containing the documents with the related document vectors.
  2. Model output Type: DocumentVectorPortObject
    A model containing node settings as well as column names of the term feature space.

  1. Sentiment Analysis (Classification) of Documents with NGram Features

    NLP Natural Language Processing
    This workflow shows how to import text from a csv file, convert it to documents, preprocess the documents and transform …
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 07_Sentiment_Classification_with_NGrams

  2. Importing, preprocessing, and classification of textual data

    NLP Natural Language Processing
    This workflow shows how to import textual data, preprocess documents by filtering and stemming, transform documents into…
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 02_Document_Classification

  3. IMDB_Sentiment_With_Viz

    Text Processing IMDB
    This workflow uses KNIME's Text Processing nodes to classify movie reviews according to sentiment. It also includes some…
    scottf > IMDB_Sentiment_With_Viz

  4. Text Mining Course: Classification

    education
    - Append color information based on class labels - Split data into training and test set - Train decision tree classifie…
    knime > Education > 02 KNIME Text Mining Course > exercises > 07 Classification

  5. Text Mining Course: Clustering

    education
    - What groups of documents are in the data? - Compute pairwise cosine distances - Apply hierarchical clustering - View d…
    knime > Education > 02 KNIME Text Mining Course > exercises > 13 Clustering

  6. Emil the TeacherBot - Extend Oracle Labels to Trainingset with k-NN

    NLP Natural Language Processing
    Once we have a subset labeled dataset by the oracle, we need to extend these classes to the whole training set. We do th…
    knime > Examples > 50_Applications > 33_Emil_the_TeacherBot > 06_AL_Extend_Expert_Classes_with_kNN

  7. Text Mining Course: Visualization

    education
    - Inspect decision tree via its view - Visualize bag of words using a tag cloud - Assign colors to terms in tag cloud. -…
    knime > Education > 02 KNIME Text Mining Course > exercises > 11 Visualization

  8. Sentiment Analysis (Classification) of Documents

    sentiment analysis text processing NLP Natural Language Processing
    This workflow shows how to import text from a csv file, convert it to documents, preprocess the documents and transform …
    knime > Examples > 08_Other_Analytics_Types > 01_Text_Processing > 03_Sentiment_Classification

  9. Guided Labeling for Document Classification

    active learning human-in-the-loop guided analytics document classification sentiment analysis topic detection tag cloud topic active learning uncertainty entropy sampling uncertainty sampling movie reviews highliting
    This workflow defines a fully automated web based application that will label your data using active learning. The workf…
    knime > Examples > 50_Applications > 57_Guided_Labeling > 01_Guided_Labeling_for_Document_Classification

  10. 02_Model_Building

    Customer Experience and Sentiment Analysis Use Case: Model Building Workflow Comments were collected from SKYTRAX which …
    knime > Examples > 50_Applications > 45_Customer_Experience_and_Sentiment_Analysis > 02_Model_Building