Intention recognition method and system, electronic equipment and readable storage medium
An intent and recognition model technology, applied in the field of deep learning, can solve the problems of poor generalization ability and high training data cost, and achieve the effect of natural interaction, cost saving, and improvement of answering speed and accuracy.
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Embodiment 1
[0047] figure 1 It is a schematic diagram of the steps of an intention identification method provided by the present invention. Such as figure 1 As shown, this embodiment discloses a specific implementation of an intent recognition method (hereinafter referred to as "method").
[0048] Specifically, the method disclosed in this embodiment mainly includes the following steps:
[0049] Step S1: using crawler technology to crawl "question-answer" data from the Internet;
[0050] Specifically, the crawled "question-answer" data includes relevant information such as question information, answer path information, and answer information, and data cleaning is performed on the crawled "question-answer" data, such as removing Irrelevant information, unifying the data format, and removing noise data, etc., finally form a standardized structural form that can be easily read by computer code.
[0051] Step S2: Identify the intent category of the answer corresponding to each question in...
Embodiment 2
[0068] Combining with the intent recognition method disclosed in Embodiment 1, this embodiment discloses a specific implementation example of an intent recognition system (hereinafter referred to as the "system").
[0069] refer to figure 2 As shown, the system includes:
[0070] Data Crawling Unit 1: Use crawler technology to crawl "question-answer" data from the Internet;
[0071] Data processing unit 2: perform data cleaning on the crawled "question-answer" data, and finally form a structure form that can be read by computer code;
[0072] Intent category determination unit 3: setting the category of intentions to be identified in combination with specific scenarios;
[0073] Intention identification unit 4: identifying the intention category of the answer corresponding to each question in the "question-answer" data through the entity recognition model, and obtaining the "question-intent" data;
[0074] Model training unit 5: using the obtained "problem-intent" data as ...
Embodiment 3
[0078] combine image 3 As shown, this embodiment discloses a specific implementation manner of a computer device. The computer device may comprise a processor 81 and a memory 82 storing computer program instructions.
[0079] Specifically, the processor 81 may include a central processing unit (CPU), or an Application Specific Integrated Circuit (ASIC for short), or may be configured to implement one or more integrated circuits in the embodiments of the present application.
[0080] Among them, the memory 82 may include mass storage for data or instructions. For example without limitation, the memory 82 may include a hard disk drive (Hard Disk Drive, referred to as HDD), a floppy disk drive, a solid state drive (SolidState Drive, referred to as SSD), flash memory, optical disk, magneto-optical disk, magnetic tape or universal serial bus (Universal Serial Bus, referred to as USB) drive or a combination of two or more of the above. Storage 82 may comprise removable or non-re...
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