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"If I have seen further, it is by standing on the shoulders of giants," IsaacNewton's renowned statement hints that new knowledge builds upon existingfoundations, which means there exists an interdependent relationship betweenknowledge, which, yet uncovered, is implied in the historical development ofscientific systems for hundreds of years. By leveraging natural languageprocessing techniques, this study introduces an innovative embedding schemedesigned to infer the "knowledge interlocking map." This map, derived from theresearch trajectories of millions of scholars, reveals the intricateconnections among knowledge. We validate that the inferred map effectivelydelineates disciplinary boundaries and captures the intricate relationshipsbetween diverse concepts. The utility of the interlocking map is showcasedthrough multiple applications. Firstly, we demonstrated the multi-step analogyinferences within the knowledge space and the functional connectivity betweenconcepts in different disciplines. Secondly, we trace the evolution ofknowledge across domains, observing trends such as shifts from "Theoretical" to"Applied" or "Chemistry" to "Biomedical" along predefined functionaldirections. Lastly, by analyzing the high-dimensional knowledge networkstructure, we found that knowledge connects each other with shorter globalpathways, and the interdisciplinary knowledge plays a critical role inaccessibility of the global knowledge network. Our framework offers a novelapproach to mining knowledge inheritance pathways in extensive scientificliterature, which is of great significance for understanding scientificdevelopment patterns, tailoring scientific learning trajectories, andaccelerating scientific progress.

Knowledge Navigation: Inferring the Interlocking Map of Knowledge from Research Trajectories