The　identification　of　the　potential　standards　essential　patents　(SEPs)　can　make　great　contributions　to　not　only　the　technology　management　theory,　but　also　to　the　real　practices　of　establishment　and　development　of　enterprise　competitiveness　and　standardization　strategy.　However,　despite　the　importance　of　identifying　potential　SEPs,　the　approaches　to　identify　potential　SEPs　lack　of　adequate　mining　of　existing　technical　standard　text　and　validation　of　identification　results　based　on　standard　updates.　Therefore,　in　this　paper,　we　contribute　to　resolving　this　issue　by　proposing　a　research　model　that　integrates　text　mining　and　the　generative　topographic　mapping　(GTM)　to　effectively　identify　and　verity　the　potential　SEPs　based　on　existing　and　updated　standards.　The　universal　terrestrial　radio　access　(UTRA)　technology　is　selected　as　a　case　study.　In　this　case,　the　TF-IDF　algorithm　and　the　Latent　Dirichlet　Allocation　(LDA)　method　are　applied　to　analyze　the　keywords　and　technical　theme　of　standard　and　patent　documents,　and　GTM　is　used　to　construct　standard　and　patent　map,　then　the　two　maps　are　mapped　by　the　improved　similarity　algorithm　we　proposed.　Finally,　39　potential　SEPs　of　the　technology　are　identified,　24　of　which　have　been　verified,　and　the　other　15　are　likely　to　be　included　in　subsequent　standard　version.　This　paper　will　contribute　to　the　identification　of　SEPs　methodology,　and　will　be　of　interest　to　UTRA　technology　research　and　development　experts.　©　2018　IEEE.