Intention recognition method and related device and equipment
A technology for identifying methods and intentions, which is applied in the field of artificial intelligence and can solve problems such as changes due to time changes
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Embodiment ( 1
[0125] see Figure 4 , Figure 4 It is a flow chart of a method for obtaining target hot text provided by the embodiment of the present application, and the method can be composed of the above-mentioned figure 2 The execution device 200, the first training device 300, the second training device 400, and the target hotspot text acquisition module 202 in the execution device 200 are executed. The embodiment of this application takes the execution device as an example for illustration. The method may include, but is not limited to, the following steps:
[0126] S100: The execution device selects a target hotspot set to which the target text belongs from multiple hotspots sets.
[0127] In one implementation, the similarity between the target text and each hot text in the first hotspot set can be calculated, and then, the similarity between the target text and each hot text in the first set is summed to obtain the target text in The similarity on this hotspot set. Wherein, th...
Embodiment ( 2
[0147] see Figure 5 , is a schematic flowchart of a neural network training method provided in the embodiment of the present application. Specifically, this method can be figure 2 The first training device 300 is shown performing. Optionally, the method may also be processed by the CPU in the first training device 300, or jointly processed by the CPU and a processor suitable for neural network calculation, which is not limited in this application. The method may include some or all of the following steps:
[0148] S202: The first training device acquires a plurality of samples, each of which includes a target hotspot text corresponding to the sample text and a real intention corresponding to the sample text.
[0149] Through the method of obtaining the target hot text corresponding to the target text described in the above embodiment (1), the target hot text corresponding to the sample text can be obtained. At this time, the sample text is the above target text.
[0150]...
Embodiment ( 3
[0162] see Figure 7 , is a schematic flowchart of another neural network training method provided in the embodiment of the present application. Specifically, this method can be figure 2 The first training device 300 is shown performing. Optionally, the method may also be processed by the CPU in the first training device 300, or jointly processed by the CPU and a processor suitable for neural network calculation, which is not limited in this application. The method may include some or all of the following steps:
[0163] S302: The first training device acquires a plurality of samples, each of which includes a target hotspot text corresponding to the sample text and a real intention corresponding to the sample text.
[0164] For the implementation of step S302, reference may be made to the specific description of step S202 above, which is not limited here.
[0165] S304: The first training device establishes an initialized first model, the first model includes an encoder a...
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