[Objective]　This　study　proposes　a　method　for　identifying　technological　evolution　paths　and　explores　key　technologies　and　branches　in　specific　domains.　It　aims　to　reveal　the　evolution　trajectories　of　technology.　[Methods]　Firstly,　we　devised　an　unsupervised　graph　embedding　model　to　integrate　patent　structural　relationships,　text　and　node　information　propagation,　and　aggregated　knowledge　into　multi-dimensional　semantic　vectors.　This　approach　expanded　the　technological　paths　while　improving　community　division　effectiveness.　Secondly,　we　proposed　methods　for　expanding　the　main　path　and　derivative　paths　from　the　perspective　of　network　topology　and　semantic　correlation.　Finally,　we　constructed　a　metric　for　technological　junction　points　to　identify　the　promising　fields.　[Results]　We　examined　the　new　method　with　drone　flight　control　system　technology　and　identified　four　subfields’technological　evolution　paths　and　branches.　We　found　that　pattern　recognition,　multiprocessor,　and　data　fusion　technologies　hold　promising　prospects.　[Limitations]　Our　identification　framework　does　not　incorporate　the　formation　mechanism　of　technological　evolution　patterns.　[Conclusions]　The　proposed　method　demonstrates　significant　advantages　in　path　expansion　effectiveness　and　application　versatility.　©　2025　Chinese　Academy　of　Sciences.　All　rights　reserved.