Extracting Hypernym-Hyponym Relationship for Financial Market Applications
Dai Zhihong1(),Hao Xiaoling1,2
1School of Information Management & Engineering, Shanghai University of Finance and Economics, Shanghai 200433, China 2Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, Shanghai 200433, China
[Objective] This paper proposes a new method to extract superior-inferior relationship from knowledge graph, and then explores its effectiveness with practical application. [Methods] First, we constructed the mapping matrix for hypernym-hyponym words and their context semantics. Then, we combined word vector similarity with the matrix to extract the relation. [Results] We examined our method with datasets of listed companies and found its F1 value was more than 3% higher than those of the existing methods. The new model could help us study the association between company similarity and stock performance. [Limitations] More research is needed to improve relationship extraction with the help of clustering technique and pattern matching method. [Conclusions] The proposed method can effectively identify the relationship between entities, and study the related listed companies and stocks. It also helps us construct better knowledge graph in the financial field.
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