About |
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Financial analysis needs factual data, but also explanation on the variability of these data. Data state facts, but provide little to no knowledge regarding how these facts materialised. The Financial Document Causality Detection Task aims to develop an ability to explain, from external sources, the reasons why a transformation occurs in the financial landscape, as a preamble to generating accurate and meaningful financial narrative summaries. Its goal is to evaluate which events or which chain of events can cause a financial object to be modified or an event to occur, regarding a given external context. This context is available in the financial news, but due to the high volatility of such information, mapping an external cause to a given consequence is not trivial. |
Summary |
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FinCausal 2020 : Shared Task: Financial Document Causality Detection will take place in Barcelona. It’s a 1 day event starting on Sep 13, 2020 (Sunday) and will be winded up on Sep 13, 2020 (Sunday). FinCausal 2020 falls under the following areas: NLP, MACHINE LEARNING, DEEP LEARNING, COMPUTATIONAL LINGUISTICS, etc. Submissions for this Workshop can be made by Apr 20, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Jul 11, 2020 to the official website of the Workshop. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the FinCausal 2020
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Credits and Sources |
| [1] FinCausal 2020 : Shared Task: Financial Document Causality Detection |
