Risk rule classification method and device based on NLP high-precision analysis label
A risk and rule technology, applied in the field of data classification processing, can solve the problem of inability to efficiently obtain the classification results of judicial risk rules
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Embodiment 1
[0024] figure 1 It is a flow chart of a risk rule classification method based on an NLP high-precision parsing tag according to an embodiment of the present invention. figure 1 As shown, the method includes the following steps:
[0025] Step S102, obtain the risk scene information.
[0026] Optionally, the risk scenario information includes: risk scenario data, risk rules.
[0027] Specifically, the embodiment of the present invention is to classify the risk rule according to the NLP parsing algorithm, and the classification results are displayed and labeled. The information of the risk scene is first required, and since the data foundation of NLP is the original data information, that is, the embodiment of the present invention. The scene information of the risk is located, where the scene information includes risk scenarios, risk rules, can also include risk parameters, risk aging, risk status, etc., resulting in the risk scene information to local or remote through data acquis...
Embodiment 2
[0042] figure 2 It is a structural block diagram of a risk rule classification device based on an NLP high-precision parsing tag according to an embodiment of the present invention, such as figure 2 As shown, the apparatus includes:
[0043] Get module 20 for acquiring risk scene information.
[0044] Optionally, the risk scenario information includes: risk scenario data, risk rules.
[0045] Specifically, the embodiment of the present invention is to classify the risk rule according to the NLP parsing algorithm, and the classification results are displayed and labeled. The information of the risk scene is first required, and since the data foundation of NLP is the original data information, that is, the embodiment of the present invention. The scene information of the risk is located, where the scene information includes risk scenarios, risk rules, can also include risk parameters, risk aging, risk status, etc., resulting in the risk scene information to local or remote through ...
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