医药制造上市公司的风险管理情报需求分析

Risk Management Intelligence Needs Analysis of Pharmaceutical Manufacturing Listed Companies

风险的本质是不确定性,情报则能够有效减少不确定性。情报工作对于具有高风险特点的医药制造上市公司的风险管理有着重要的价值,而情报工作的首要任务便是情报需求分析。为了提升情报需求分析的效率、准确性、主动性、客观性和自动化水平,本文利用自然语言处理、机器学习和文本挖掘等智能化的技术手段,从文本数据资源中分析用户的情报需求。对A股医药制造上市公司在年报中披露的风险信息进行采集,基于向量空间模型、TF-IDF方法和K-Means聚类算法来分析医药制造上市公司的风险管理情报需求。

The essence of risk is uncertainty, and intelligence can effectively reduce uncertainty. Intelligence work is of great value to risk management of listed pharmaceutical manufacturing companies with high risk characteristics, and the primary task of intelligence work is intelligence needs analysis. In order to improve the efficiency, accuracy, initiative, objectivity and automation level of intelligence needs analysis, this paper uses intelligent technologies such as natural language processing, machine learning and text mining to analyze users’ intelligence needs from text data resources. This paper collects the risk information disclosed by A-share pharmaceutical manufacturing listed companies in annual reports, and analyzes the risk management intelligence needs of pharmaceutical manufacturing listed companies based on vector space model, TF-IDF method and K-Means clustering algorithm.