
      The Reuters-21578 benchmark corpus, ApteMod version

This is a publically available version of the well-known Reuters-21578
"ApteMod" corpus for text categorization.  It has been used in
publications like these:

 * Yiming Yang and X. Liu. "A re-examination of text categorization
   methods".  1999.  Proceedings of 22nd Annual International SIGIR.
   http://citeseer.nj.nec.com/yang99reexamination.html

 * Thorsten Joachims. "Text categorization with support vector
   machines: learning with many relevant features".  1998. Proceedings
   of ECML-98, 10th European Conference on Machine Learning.
   http://citeseer.nj.nec.com/joachims98text.html

ApteMod is a collection of 10,788 documents from the Reuters financial
newswire service, partitioned into a training set with 7769 documents
and a test set with 3019 documents.  The total size of the corpus is
about 43 MB.  It is also available for download from
http://kdd.ics.uci.edu/databases/reuters21578/reuters21578.html ,
which includes a more extensive history of the data revisions.

The distribution of categories in the ApteMod corpus is highly skewed,
with 36.7% of the documents in the most common category, and only
0.0185% (2 documents) in each of the five least common categories.
In fact, the original data source is even more skewed---in creating
the corpus, any categories that did not contain at least one document
in the training set and one document in the test set were removed from
the corpus by its original creator.

In the ApteMod corpus, each document belongs to one or more
categories.  There are 90 categories in the corpus.  The average
number of categories per document is 1.235, and the average number of
documents per category is about 148, or 1.37% of the corpus.

 -Ken Williams
  ken@mathforum.org

         Copyright & Notification 

(extracted from the README at the UCI address above)

The copyright for the text of newswire articles and Reuters
annotations in the Reuters-21578 collection resides with Reuters Ltd.
Reuters Ltd. and Carnegie Group, Inc. have agreed to allow the free
distribution of this data *for research purposes only*.  

If you publish results based on this data set, please acknowledge
its use, refer to the data set by the name "Reuters-21578,
Distribution 1.0", and inform your readers of the current location of
the data set (see "Availability & Questions").

