readme.md

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-<h1>Parallel clustering with a k-medoids algorithm</h1>
-
-<p>Joint work with <a href="http://eric.univ-lyon2.fr/~jcugliari/">Jairo Cugliari</a>.</p>
-
-<hr/>
-
-<p>This C program runs the k-medoid algorithm on several subsets of one (presumably big) dataset. 
-The computed medoids are then merged iteratively, until we get a final set of k centers.</p>
-
-<hr/>
-
-<p>The folder "communication/" contains latex sources (and generated pdf files) of a short paper submitted 
-to the Journées de Statistique in Rennes, France (2014), and also the slides presented at this event.</p>
-
-<p>The other folder contains all the C code; but not the EDF (french electricity company) datasets, because they 
-are not public. Since the (de)serialization process in code/src/TimeSeries/ is tailored for these data, 
-it is necessary to adapt this small part of the code to use any other custom time-series files.</p>

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+# Parallel clustering with a k-medoids algorithm
+
+Joint work with [Jairo Cugliari](http://eric.univ-lyon2.fr/~jcugliari/)
+
+---
+
+This C program runs the k-medoid algorithm on several subsets of one (presumably big) dataset. 
+The computed medoids are then merged iteratively, until we get a final set of k centers.
+
+---
+
+The folder "communication/" contains latex sources (and generated pdf files) of a short paper submitted 
+to the Journées de Statistique in Rennes, France (2014), and also the slides presented at this event.
+
+The other folder contains all the C code; but not the EDF (french electricity company) datasets, because they 
+are not public. Since the (de)serialization process in code/src/TimeSeries/ is tailored for these data, 
+it is necessary to adapt this small part of the code to use any other custom time-series files.