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<title>Bag of words</title>
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<h1>Bag of words</h1>

<img class="screenshot" src="../icons/BagOfWords.png">
<p>Construct the bag-of-words representation of documents.</p>



<DL class=attributes>
<DT>Examples (ExampleTable)</DT>
<dd>Attribute-valued data set.</dd>

<DL class=attributes>
<DT>Examples (ExampleTable)</DT>
<DD>Attribute-valued data set with words as metaatributes.</DD>


<p>The bag of words widget is used to construct the bag-of-words representation
of documents. It does so by adding words as metaatributes to each document. The
values corresponding to words are chosen in the TFIDF box. If None is selected,
then the value corresponding to a metaatribute is the frequency of that metaatribute (word)
in the particular document. If log(1/f) is chosen, then the value corresponding
to a metaatribute is the TFIDF value of that metaatribute (word) in the particular
document. The normalization box gives the possibility to normalize the lengths of
documents in the collection. If None is chosen, no normalization is used. Option
L1 normalizes the lengths of documents using the Manhattan norm, whereas L2 option
normalizes lengths using Euclidean norm. Info box displays the number of documents
in the collection and the name of the text attribute.</p>

<a href="BagOfWords.png"><img class="schema" src="BagOfWords.png" alt="Bag of words widget"></a>


<p>Below is a simple example how to use this widget. The input is fed
from the <a href="Preprocess.htm">Preprocess</a> widget, and the output
is sent to the <a href="TextFeatureSelection.htm">Feature selection</a> widget.</p>

<a href="BagOfWords-Example.png"><img src="BagOfWords-Example.png" alt="Schema with BagOfWords"