Disturbance information judgment method and system based on NER and NLU
A technology of information judgment and text information, applied in the field of information recognition, can solve problems such as inability to achieve low-cost updates, inability to achieve rapid response, time-consuming and energy-consuming, etc., and achieve small errors, low compatibility characteristics, and accurate recognition rates. Effect
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Embodiment 1
[0024] Such as figure 1 As shown, the embodiment of the present application provides a method for judging harassment information based on NER and NLU, wherein the method includes:
[0025] Step S100: Obtain first text information;
[0026] Specifically, the first text information is the source text information that needs to be judged, including information, email, instant chat software (IM), etc. If the source information is voice, it will be converted into text through audio recognition and text conversion technology. information.
[0027] Step S200: Perform natural language understanding processing on the first text information to obtain natural language understanding intent list information;
[0028] Specifically, the natural language understanding (NLU, Natural Language Understanding) refers to a mapping from natural language to the inside of the machine, which means that the machine can perform certain language functions expected by humans, and the natural language unde...
Embodiment 2
[0077] Based on the same inventive concept as the method for judging harassment information based on NER and NLU in the foregoing embodiments, the present invention also provides a judging system for harassment information based on NER and NLU, such as figure 2 As shown, the system includes:
[0078] A first obtaining unit 11, the first obtaining unit 11 is configured to obtain first text information;
[0079] A second obtaining unit 12, the second obtaining unit 12 is configured to perform natural language understanding processing on the first text information, and obtain natural language understanding intent list information;
[0080] A third obtaining unit 13, the third obtaining unit 13 is configured to perform named entity recognition on the first text information, and obtain word slot content information;
[0081] A fourth obtaining unit 14, the fourth obtaining unit 14 is configured to obtain the first result information according to the natural language comprehension...
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