With　the　rapid　developments　in　science　and　technology,　technologies　from　various　fields　are　increasingly　converging.　Technology　convergence　has　become　a　primary　source　of　disruptive　technologies　(DTs).　Revealing　the　mechanisms　of　technology　convergence　in　DTs　and　identifying　their　evolutionary　pathways　and　trends　are　of　great　significance　for　the　enterprise＇s　R&D　strategic　decision-making　and　the　government＇s　innovation　policy　formulation.　Previous　studies　on　the　evolutionary　pathways　of　technology　convergence　have　mainly　relied　on　citation　information　and　International　Patent　Classification　(IPC)　coclassification　analysis.　However,　measuring　technology　convergence　using　patent　citation　information　has　a　time　lag,　and　patent　IPC　codes　fail　to　capture　microtechnological　changes.　Moreover,　technology　roadmapping　(TRM)　is　widely　recognized　as　a　valuable　method　for　studying　evolutionary　pathways　and　offering　a　systematic　approach　to　mapping　the　evolution　of　functions　or　performance　in　DTs.　However,　existing　TRM　methods　have　mainly　relied　on　expert　opinion,　which　is　a　time-consuming　and　costly　approach.　Therefore,　in　this　article,　we　integrated　patent　coclassification　analysis,　subject-action-object-prepositional　phrase　semantic　analysis,　and　TRM　to　propose　a　framework　for　monitoring　DTs＇　evolutionary　pathways,　revealing　the　technology　convergence　characteristics　of　DTs　and　identifying　their　trends.　We　employed　smartphones　as　a　case　study　to　demonstrate　the　validity　and　flexibility　of　this　framework.　This　article　provides　a　novel　approach　for　roadmapping　DTs＇　evolutionary　pathways　and　reveals　the　technology　convergence　characteristics　in　the　emergence　of　DTs,　thereby　aiding　the　comprehension　of　DTs＇　emergence　and　development　trends.　This　article　also　will　be　of　interest　to　experts　in　smartphone　technology　R&D.