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This application discloses a human resource allocation method and system based on multi-source employment demand, relating to the field of knowledge graph technology. The method includes: acquiring employment task types and multi-dimensional task demand information; obtaining family-of-tasks and family-of-task demand information; and extracting neighboring task groups and neighboring task demand information groups; generating multi-dimensional capability parameters; processing and acquiring human resource matching degree, matched human resource information, and matched multi-dimensional capability parameters; and extracting neighboring human resource information groups and neighboring multi-dimensional capability parameter groups; performing derivative task matching analysis to obtain derivative human resource matching degree; and optimizing human resources based on the human resource matching degree and derivative human resource matching degree to obtain optimal human resource information for allocation. This application solves the technical problems of existing human resource allocation methods lacking the ability to predict potential derivative tasks and exhibiting information silos between the human resource database and the task database, leading to low matching efficiency and accuracy.