Interpretable financial subject matter generation method and device fusing emotion, industrial chain and cause logic
An industrial chain and subject matter technology, applied in the field of interpretable subject matter generation devices, can solve problems such as insufficient application exploration, weak interpretability of the reasoning process, and inability to visualize the reasoning path, so as to improve the ability of logical reasoning and alleviate the influence of trends The effect of unreliability
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[0059] 1) Extraction based on rules. This method mainly realizes the clause-level causal extraction model by collecting and arranging causal trigger words and constructing rule templates based on trigger words. Among them, a clause is the shortest text description sentence segmented by commas, semicolons, periods, question marks, and exclamation marks in the text. An example of the results extracted by rules is shown in Table 1.
[0060] Table 1 - Example of rule template and extraction result
[0061]
[0062] 2) Extraction based on sequence labeling model. The present invention adopts the model structure of BERT+BiLSTM+CRF. In the design of the sequence label, the sequence label of the model adopts the BIO label system, and the label types are mainly cause (reason), trigger (causal trigger word), and effect (result). In the construction of the data set, the present invention adopts the method of template pre-marking + manual correction to construct the explicit causal ...
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