That algorithm builds a frequent pattern tree, which is then used to extract the message clustering patterns, which in turn identify the campaigns [12,17].
In this way, extra messages from cluster controller CC ij enable to load balance between active cluster controller.
The upper bound on the number of messages for cluster merging is equal to the average number of members per cluster, which is kTB, kWB and kPB for TB, WB and PB techniques respectively.
Thus, it uses its energy to forward only one message to cluster 1, although it would have been possible to forward messages from T 1,i, i∈I K ∖{1} to cluster 1 had the relay in any data from these nodes.
The interested reader may verify that the message from cluster j to cluster j + 1 during a run of max-sum message passing with C m as the root of T equals for j > 1, (1) M j (R j ∩ j + 1 ) = max h j max R j \ j + 1 (∑ i : r i ∈ R j log P (o i j | r i, h j ) + M j − 1 (R j − 1 ∩ j ) ), and for j = 1, M 1 (R 1 ∩ 2 ) = max R 1 \ 2 (∑ i : r i ∈ C 1 log P (o i 1 | r i, h 1 = 0 ) ).
categorise messages - clustering together receipts or bank statements for instance.
Watson Workspace magically organizes past messages into clusters and even extracts summaries and action items.
However, it still has to spend some energy to forward node T 1,1's message to cluster 1.
Cluster head and gateway node forwards (manage) the message for cluster member, so power consumption of such nodes is higher compared to cluster member nodes.
The objective function is a maximization of similarity between messages in clusters, which is defined by (k -nearest neighbor ((k -nearestrithm.
