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基于知識圖譜技術(shù)的上市企業(yè)產(chǎn)業(yè)鏈風(fēng)險(xiǎn)預(yù)測
網(wǎng)絡(luò)安全與數(shù)據(jù)治理 9期
董士豪,鄭朗,王特,于曉娟,王耀君
(中國農(nóng)業(yè)大學(xué)信息與電氣工程學(xué)院,北京100038)
摘要: 隨著產(chǎn)業(yè)互聯(lián)網(wǎng)的飛速發(fā)展,面對海量的產(chǎn)業(yè)數(shù)據(jù),構(gòu)建知識圖譜等自然語言處理應(yīng)用需求逐漸增長。產(chǎn)業(yè)信息的有效管理和挖掘有助于及時(shí)發(fā)現(xiàn)所面臨的風(fēng)險(xiǎn)和機(jī)遇,產(chǎn)業(yè)鏈風(fēng)險(xiǎn)預(yù)測可以為監(jiān)管部門提供產(chǎn)業(yè)風(fēng)險(xiǎn)預(yù)警手段。針對以上問題,本文以知識圖譜相關(guān)知識為科學(xué)依據(jù),提出了基于知識圖譜技術(shù)的產(chǎn)業(yè)文本數(shù)據(jù)實(shí)體標(biāo)注準(zhǔn)則,對海量上市公司產(chǎn)業(yè)信息進(jìn)行知識抽取,形成自上而下的三維產(chǎn)業(yè)知識圖譜。同時(shí)研究了上市企業(yè)產(chǎn)業(yè)知識圖譜特定產(chǎn)業(yè)鏈知識的內(nèi)在聯(lián)系,總結(jié)規(guī)律并結(jié)合產(chǎn)業(yè)鏈往年時(shí)序圖特征信息實(shí)現(xiàn)圖譜推理,成功的對產(chǎn)業(yè)鏈中上市企業(yè)市值等信息進(jìn)行了預(yù)測和分析。
中圖分類號:F830
文獻(xiàn)標(biāo)識碼:A
DOI:10.19358/j.issn.2097-1788.2023.09.004
引用格式:董士豪,鄭朗,王特,等.基于知識圖譜技術(shù)的上市企業(yè)產(chǎn)業(yè)鏈風(fēng)險(xiǎn)預(yù)測[J].網(wǎng)絡(luò)安全與數(shù)據(jù)治理,2023,42(9):21-28.
Risk prediction of the industrial chain of listed enterprises based on knowledge graph technology
Dong Shihao,Zheng Lang,Wang Te,Yu Xiaojuan,Wang Yaojun
(College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)
Abstract: With the rapid development of the industrial Internet, the demand for natural language processing applications such as building knowledge graphs is gradually increasing in the face of massive industrial data. The effective management and mining of industrial information can help to discover the risks and opportunities faced in time, and the risk prediction of the industrial chain can provide regulatory authorities with early warning means for industrial risks. In view of the above problems, this paper takes the knowledge related to knowledge graph as the scientific basis, and puts forward the criteria for labeling industrial text data entities based on knowledge graph technology, extracts knowledge from massive listed companies′ industrial information, and forms a topdown threedimensional industrial knowledge map. At the same time, the intrinsic relationship of specific industrial chain knowledge of listed enterprises in the industrial knowledge graph is studied, the law is summarized, and the graph reasoning is realized by combining the characteristic information of the time series chart of the industrial chain in previous years, and the market value of listed enterprises in the industrial chain is successfully predicted and analyzed
Key words : knowledge graph; industry chain analysis; risk prediction; entity relationship callouts

0    引言

產(chǎn)業(yè)知識圖譜是結(jié)構(gòu)化的產(chǎn)業(yè)語義知識庫,通過形式化描述產(chǎn)業(yè)領(lǐng)域的概念、實(shí)體、屬性及其相互關(guān)系,使概念、實(shí)體間相互聯(lián)結(jié),構(gòu)成網(wǎng)狀知識結(jié)構(gòu)。產(chǎn)業(yè)涉及范圍廣泛,本研究以產(chǎn)業(yè)大類中的上市企業(yè)、基金、上市企業(yè)業(yè)務(wù)鏈、產(chǎn)業(yè)鏈、基金經(jīng)理和股東等為研究對象,形成了知識覆蓋面廣、數(shù)據(jù)更新實(shí)時(shí)、精準(zhǔn)度高的自上到下的三維度產(chǎn)業(yè)知識圖譜。根據(jù)中國產(chǎn)業(yè)經(jīng)濟(jì)信息網(wǎng)和中國證券業(yè)協(xié)會規(guī)定的18大類產(chǎn)業(yè)為第一維度知識;以上市企業(yè)、基金、基金經(jīng)理和股東組成的第二維度知識;再到第三維度的公司業(yè)務(wù)鏈知識,最終完成了產(chǎn)業(yè)知識圖譜的構(gòu)建。根據(jù)研究目標(biāo)及思路,下文確定了數(shù)據(jù)獲取方向和主要的獲取方法。



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作者信息:

董士豪,鄭朗,王特,于曉娟,王耀君

(中國農(nóng)業(yè)大學(xué)信息與電氣工程學(xué)院,北京100038)


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