[目的/意義]情報研究知識庫的構建不僅需要依賴現有的知識庫構建方法與技術來實現,而且需要針對情報研究目標對關鍵技術進行擴展與創新。[方法/過程]文章利用自然語言處理和深度學習的方法,探究情報研究知識庫構建中用于文本知識抽取和組織的文本語義空間技術以及用于專家定位的專家知識地圖技術。[結果/結論]文章提出包含文本集、特征詞貢獻集和特征詞語義關聯集的文本語義空間,以及包含領域術語關聯和專家合作關聯的專家知識地圖,詳細闡述具體步驟并以石墨烯領域數據進行實現。

[Purpose/significance]The construction of intelligence analysis knowledge base needs to not only rely on the existing knowledge base construction methods and technologies,but also expand and innovate the key technologies in specific to the information research target. [Method/process] Using the methods of natural language processing and deep learning,this paper explores the text semantic space technology for text knowledge extraction and organization and expert knowledge map technology for expert positioning in the construction of intelligence analysis knowledge base. [Result/conclusion] The paper puts forward the text semantic space including text set,term contribution set and term semantic association set,as well as expert knowledge map including domain terminology association and expert cooperation association. The specific steps are described in detail and experiment is conducted by using graphene field data.