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Constructing Big Data Platform for Sci-Tech Knowledge Discovery with Knowledge Graph |
Jiying Hu1,Jing Xie1,2(),Li Qian1,2,Changlei Fu1 |
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China 2Department of Library, Information and Archives Management, University of Chinese Academy of Sciences, Beijing 100190, China |
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Abstract [Objective] This paper tries to create a big data platform for sci-tech knowledge discovery, aiming to transform the keyword-based literature retrieval to knowledge retrieval. [Methods] First, we extracted and annotated scientific research entities and calculated their relationship with data mining techniques. Then, we created distributed indexes based on entity knowledge graph, which achieved multi-dimensional knowledge retrieval and correlated navigation. [Results] This study generated knowledge graphs for 10 research entities, such as papers, projects, scholars and institutions, etc. The proposed platform could conduct intelligent semantic search and multi-dimensional knowledge discovery with these knowledge graphs. [Limitations] Our study is at the entity level, and more research is needed for the semantic retrieval. [Conclusions] The proposed platform organizes data at the knowledge level, which meets user’s precise knowledge retrieval demands and improves user experience.
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Received: 03 December 2018
Published: 04 March 2019
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