本文選題：關(guān)系圖譜 + 知識圖譜��； 參考：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：在互聯(lián)網(wǎng)+大數(shù)據(jù)時代,決策日益基于數(shù)據(jù)和分析做出,而非經(jīng)驗(yàn)和直覺。近年來,隨著信貸、消費(fèi)等領(lǐng)域個人“用戶畫像”的成功應(yīng)用,如何對資本市場企業(yè)和人物對象進(jìn)行全方位、多角度的模型刻畫正在成為金融監(jiān)管和投融資的一個新熱點(diǎn)。本文基于作者在證券交易所的實(shí)際開發(fā)項(xiàng)目,針對資本市場中證券交易所的監(jiān)管需求,設(shè)計(jì)并實(shí)現(xiàn)了一個以資本市場人物和企業(yè)關(guān)系圖譜為主要數(shù)據(jù)模型的信息系統(tǒng)。本文研究的人物和企業(yè)關(guān)系圖譜是知識圖譜技術(shù)在資本市場這一垂直領(lǐng)域的應(yīng)用。知識圖譜技術(shù)自從2012年Google發(fā)布以來,其在改進(jìn)搜索引擎服務(wù)質(zhì)量和效率方面作用明顯。本文參考知識圖譜技術(shù)的通用構(gòu)建框架,提出了以實(shí)體獲取和實(shí)體關(guān)系抽取為主要手段的關(guān)系圖譜構(gòu)建方案。在實(shí)體獲取方面,應(yīng)用深度學(xué)習(xí)技術(shù),以長短時記憶學(xué)習(xí)網(wǎng)絡(luò)作為語料特征學(xué)習(xí)模型,以條件隨機(jī)場為序列標(biāo)注模型,構(gòu)建了在文本語料中識別命名實(shí)體的方案;在實(shí)體關(guān)系抽取方面,結(jié)合領(lǐng)域知識和業(yè)務(wù)需求,從公司公告年報(bào)等半結(jié)構(gòu)化數(shù)據(jù)中以規(guī)則匹配抽取實(shí)體關(guān)系。此外,設(shè)計(jì)并實(shí)現(xiàn)了關(guān)系圖譜在系統(tǒng)中的查詢展示功能,提供了良好的可視化及交互性。本文對于資本市場人物和企業(yè)關(guān)系圖譜的設(shè)計(jì)實(shí)現(xiàn)是基于多源異構(gòu)數(shù)據(jù)的模型,具有信息價值密度大,抽象層次高以及應(yīng)用范圍廣的特點(diǎn)。該業(yè)務(wù)可以廣泛服務(wù)于證券交易所的上市公司持續(xù)監(jiān)管、市場監(jiān)察與執(zhí)法、以及發(fā)行審核與投融資對接等業(yè)務(wù),對中國多層次資本市場建設(shè)具有重要的支持價值。
[Abstract]:In the age of big data, decisions are increasingly based on data and analysis, rather than experience and intuition. In recent years, with the successful application of personal "user portrait" in the fields of credit, consumption and other fields, how to carry out all-round and multi-angle model portrayal of capital market enterprises and people is becoming a new hot spot in financial supervision and investment and financing. Based on the author's actual development project in the stock exchange, this paper designs and implements an information system based on the capital market figures and enterprise relationship atlas, aiming at the regulatory needs of the stock exchange in the capital market. The relationship map of people and firms is the application of knowledge map technology in the vertical field of capital market. Knowledge map technology has played an important role in improving the service quality and efficiency of search engine since the publication of Google in 2012. Referring to the general construction framework of knowledge atlas technology, this paper proposes a scheme of building relational atlas, which mainly uses entity acquisition and entity relation extraction as the main means. In the aspect of entity acquisition, the method of identifying named entity in text corpus is constructed by using depth learning technology, long and short memory learning network as corpus feature learning model and conditional random field as sequence tagging model. In the aspect of entity relation extraction, combined with domain knowledge and business requirement, entity relationship is extracted from semi-structured data such as annual report of company announcement by rule matching. In addition, the query and display function of relational atlas in the system is designed and realized, which provides good visualization and interactivity. In this paper, the design and implementation of capital market relationship atlas is based on a multi-source heterogeneous data model, with the characteristics of high information value density, high abstract level and wide application range. This business can be widely used in the continuous supervision of listed companies, market supervision and law enforcement, as well as the combination of issuance and audit with investment and financing, which has important support value for the construction of multi-level capital market in China.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP311.52

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