  Merger trees track the evolution of halos across multiple snapshots. They
assign for halos of a particular snapshot, the set of halos from previous
snapshots they possibly originated from. In this work, Association rule
analysis a well known technique from data mining has been used to build halo
merger trees. Association rule analysis tries to find associations between
different halos(in same as well as in snapshots) using the particle IDs of the
particles which the halos are made of. Associations are expressed in the form
of association rules. Merger trees are one of the several useful results one
can obtain from the output of association rule analysis. Other results
including halo substructure and halo splitting can also be extracted. Each type
of output to be extracted from the association rule analysis output correspond
to a pattern in association rules. Merger trees were formed and tested using
the above technique. Dark matter simulations were run using Gadget-2 for 128^3
particles. Halos were extracted from the simulation snapshots using Amiga Halo
Finder. Halo accretion history was plotted and compared against those formed
using AHF merger tree builder.
