Overall process for clustering AOL sessions
===========================================

Remove queries that are just ‘-‘
> awk '!/\t-\t/' fullcollection.1000000 > fullcollection.1000000.filtered


Extract the feature vectors:
> python parseN.py -v fullcollection.1000000


Select a sample from the output.log:
> python selectRandomVectors.py output.log -s 100000 > 100000.sample1
(times N)

Edit the ARFFheader to suit the data 
(textedit)

Prepend the appropriate weka header
> cat ARFFheader 100000.sample1 > ARFF/100000.sample1.arff
(times N)

Apply feature scaling:
> python normalise_sessions.py ARFF/100000.sample1.arff > ARFF/100000.sample1.norm.arff
(times N)

Cluster using weka