Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique

Algorithm 1

Pseudocode/Algorithm of the Proposed System.

Input Documents as doc

OutPut Clusters as preCluster

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Processing for Pooling and SDR

Function PoolSDR()

for d in docs:

  wtSet=(word_tokenize(d))

  for t in wtSet:

   ww=sentiwordnet.senti_synsets(t)

   if len(ww)>0 and t not in stop_words:

    for w in ww:

      if w.synset[0]. in bucketArray:

       bk=[i, t,bucketArray.index(w.synset.name())]

       bucket.append(bk)

       if len(bucket)>8:

        break

      else:

       bucketArray.append(w.synset.name())

       bk=[i, t,bucketArray.index(w.synset.name())]

       bucket.append(bk)

       if len(bucket)>8:

        break

     end if

    end if

    end for

   end if

  end for

end for

end function

Process for Clustering

Function Cluster()

i=1

Cluster=""

for b in bucket:

  if (b[0]==i):

   Cluster=str(Cluster) + " + str(b[2])

  else:

   preCluster.append(Cluster)

   Cluster=""

   i=i+1

   Cluster=str(Cluster) + "" + str(b [2])

  end if

end for

end function