Group　identification　refers　to　discovering　groups　with　similar　behaviors　or　preferences.　The　daily　trajectories　record　the　activities　of　moving　objects,　which　reflect　their　behaviors.　These　mobile　data　provide　us　with　a　new　data　analysis　approach　for　groups　identification.　Therefore,　we　can　identify　users　or　groups　based　on　similar　trajectory　patterns　by　mining　implicit　behaviors　patterns.　In　this　paper,　we　propose　a　novel　trajectory　semantics　calculation　method　to　identify　groups　that　have　similar　behaviors.　In　our　model,　we　first　propose　a　fast　and　efficient　two-phase　discovering　stay　regions　method　(TPD)　from　daily　trajectories,　then　generate　semantic　trajectories　by　enriching　the　stay　regions　with　semantic　labels　based　on　POI　information　and　LDA　topic　model.　To　measure　the　similarity　between　semantic　trajectories,　we　design　a　semantic　similarity　measure　model　based　on　geographic　and　semantic　similarity　factor.　We　have　conducted　extensive　experiments　on　real　trajectory　dataset　of　Geolife　project,　and　the　experimental　results　show　our　proposed　method　is　both　effective　and　efficient.