非结构化智能金融投研平台的开发与行业应用

Development and Business Application of Unstructured Intelligent Financial Investment-research Platform

当前针对非结构化数据处理的研究多集中于实验态的技术实现,对于其在金融投研业务中落地应用的整体架构与路径的研讨则较为缺乏.为此,提出将大数据、自然语言处理、知识图谱等技术结合起来进行智能化投研平台的研发设计,并实现其在真实金融投研场景的应用.该平台基于Hadoop分布式系统进行数据采集、存储与计算,集成了传统文本处理技术及主流AI算法,形成了投研相关的深度语义理解能力,一是高效提取出金融文本信息,并以知识图谱的形式存储;二是基此进一步挖掘预测,输出金融投研领域的智能化分析服务.以金融研究中城投债相关文本作为测试样例,验证了平台运行效果,结果表明平台能以较高的准确率全流程、自动化地实现各项功能,提升金融投研领域的工作效率.

Current research on unstructured data processing focuses on technological realization in experiments,while the discussions on the overall architecture and the practical application path in financial investment-research businesses are far from enough.Considering this,this study proposes to develop and design the intelligent investment-research platform through the combination of big data,natural language processing(NLP),and knowledge graph(KG)and implements the platform in real financial investment-research scenarios.With the data collecting,storage,and computation operated through the distributed system Hadoop,the platform integrates traditional text processing technologies and mainstream AI algorithms to form a deep semantic understanding capacity.As a result,the platform is capable of extracting financial text efficiently and storing the information in the form of KGs,and it can also provide intelligent analysis in financial investment research by further exploration and prediction.Taking the tests related to municipal bonds as samples,this research has proved the validity of this platform.The results show that the platform can automatically perform various functions with high precision through the whole process,thus promoting the working efficiency in financial investment research.