Name
Abstract | ||
|---|---|---|
In this research, we extract causal information from textual data and construct a causality database in the economic field. We develop a method to produce causal chains starting from phrases representing specific events. The proposed method can offer possible ripple effects and factors of particular events or situations. Using our approach to Japanese textual data, we have implemented a prototype system that can display causal chains for user-entered words. A user can interactively edit the causal chains by selecting appropriate causalities and deleting inappropriate causalities. The economic causal-chain search algorithm can be applied to various financial information services. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/978-3-030-56150-5_2 | IJCAI |
Keywords | DocType | Citations |
Natural language processing,Economic causal-chain,Financial text mining | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kiyoshi Izumi | 1 | 127 | 37.12 |
| Hiroki Sakaji | 2 | 30 | 17.97 |