Text Mining with Information Extraction for Chinese Financial Knowledge Graph

Financial Documents reveal important financial information about a company's financial performance which plays a vital role not only to the stakeholders but also to the public. Therefore, many researchers utilize dynamic Text mining methods in financial document to identify, analyze, predict or evaluate a company's future financial value. In order to find deeply the relationship between companies and the stakeholders, provide a simplified method for them to identify the future financial performance of the corporation. In this paper, we present a Chinese Information Extraction System (CFIES) for Financial Knowledge Graph (FinKG). The major findings of the research show an increased importance of the key audit matters in finance. The major research contribution of this paper is that we have developed CFIES which can extract the tuples from the financial reports. The adoption of the information system can assist the development of a knowledge graph that can discover deep financial knowledge in the finance domain. The managerial implication is that building CFIES can efficiently enable us to clarify the complicated relationship between the corporations, board of directors, investors, and especially the asset, assisting the stakeholders to discover a new financial knowledge representation and to make a financial decision.