Processing　application　user　reviews　has　recently　been　recognized　as　an　efficient　approach　to　explore　user　requirements.　However,　most　existing　approaches　focus　on　mining　the　reviews　themselves　without　effectively　associating　the　reviews　with　requirements　concepts,　limiting　the　effectiveness　of　review　mining　for　requirements　analysis　tasks.　In　this　paper,　we　propose　to　automatically　identify　Requirements-oriented　Reviews　(RoRs)　from　software　application　reviews　by　considering　requirements　specific　domain　knowledge　and　syntactic　information　of　user　reviews.　Specifically,　we　first　define　a　conceptual　model　of　RoRs　based　on　existing　requirements　ontology　and　user　review　categories,　establishing　connections　between　the　concepts　of　requirements　engineering　and　user　reviews.　We　then　systematically　identify　the　textual　features　of　RoRs　by　following　a　conceptual　model-driven　top-down　strategy.　Based　on　such　features,　we　then　train　effective　RoR　classifiers　to　identify　RoRs.　To　evaluate　the　performance　of　our　approach,　we　have　applied　our　approach　to　a　real　dataset　of　mobile　application　reviews,　the　results　of　which　show　that　our　approach　can　effectively　identify　RoRs　with　an　F-measure　of　0.8,　outperforming　than　the　baselines.