Getting Started with Orange 19 How to Import Text Documents Video Lecture

In the previous videos we talked about text preprocessing,
clustering and classification.
We worked with Grimm's tales, a data set I have prepared in a spreadsheet.
But working with spreadsheets and long text can be a pain.
Is there any other way we can import texts into Orange?
Of course there is!
This time I will work with Kennedy's speeches.
I have 17 of them in a Kennedy folder,
each in its own file.
Files can be Word documents, PDFs or plain text files.
Here for example is a speech from Democratic National Convention.
To load corpus into Orange
open Text add-on,
place Import Documents widget on a canvas,
and open it.
Click on the folder icon
and select the folder you wish to import.
Let us observe our data in a Corpus Viewer.
Here's the speech we've seen earlier.
Now we can do some clustering.
I'll use Preprocess Text,
Bag of Words,
Distances,
and Hierarchical Clustering.
I was fast.
For details on text preprocessing and clustering
you can check our previous videos.
Looks like I have two interesting clusters:
one on nuclear arms
and the other with Kennedy's presidential addresses.
Clustering is fine, but what about classification?
Can I tell Orange some documents belong to one group
and others to the other?
Let us put Kennedy speeches into two folders.
say 'pre-1962'
and 'post-1962'.
Now, reload the folder.
Orange recognized subfolders as class categories.
If we observe the corpus in a data table,
we can see that Orange put 'pre-1962'
and 'post-1962' in the gray class column.
You can check our previous videos on text classification
to learn how to proceed.
Import Documents makes it so much easier to organize your files in your research.
Today we've learned how to import our own data for text analysis
and how to define class values from scratch.