Ranking　similar　structure　groups/subgraphs　can　contribute　to　importantly　practical　applications,　such　as　finding　the　most　suspicious　tax　evasion　group　within　a　heterogeneous　information　network.　This　problem,　however　lacks　attentions　in　the　current　research　community.　Inspired　by　social　network　analysis,　this　paper　coins　a　definition　of　a　taxpayer　interest　interacted　network　(TPIIN),　in　which　persons　or　companies　act　as　nodes　as　well　as　the　arcs　act　as　the　relationships　between　persons　and/or　companies,　and　the　weight　of　an　arc　is　equal　to　the　interest　affiliated　degree　(IAD)　of　a　direct　tie　or　link　according　to　various　economic　behaviors　between　persons　and/or　companies.　Moreover,　we　adopted　four　operations,　Maximum,　Minimum,　Addition,　and　Multiply,　to　calculate　the　IAD　of　a　trail,　then　propose　a　voting　algorithm　based　on　the　four　operations　to　compare　the　suspicion　degrees　of　all　groups　containing　the　same　trading　relationship　arc.　Experiments　are　carried　out　and　their　results　verify　the　proposed　method.