[Objective] This paper aims to improve the scientific literature retrieval system with the help of semantic recognition and knowledge relationship computing. [Methods] First, we identified and extracted semantic objects from the scientific literature. Then, we calculated and established semantic relations among the objects using data-mining tools. Finally, we built semantic multidimensional index for these objects and relations, and then designed a new data organization model. [Results] The new system effectively identified the semantic information and improved the user experience. [Limitations] We need to expand the dataset used in this study and evaluate the new system in other areas. [Conclusions] The proposed system could retrieve more knowledge and indicate some future directions.
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