Man-machine interaction method and device based on semantic net and intention recognition and medium

A technology of human-computer interaction and semantic web, which is applied in the field of human-computer interaction based on semantic web and intent recognition, can solve the problems of lack of training corpus for recognition, the inability to extract entities and attributes, and the inability to accurately locate problems, so as to improve the quality of question and answer Effect

Pending Publication Date: 2020-12-11
杭州远传新业科技股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, this patent application requires a knowledge map constructed from a large amount of corpus, and the current general entity recognition model can only recognize names of people, places, and institutions, etc., and lacks training corpus for the recognition of professional entitie

Method used

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  • Man-machine interaction method and device based on semantic net and intention recognition and medium
  • Man-machine interaction method and device based on semantic net and intention recognition and medium
  • Man-machine interaction method and device based on semantic net and intention recognition and medium

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Experimental program
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Effect test

Embodiment 1

[0061] This embodiment provides a human-computer interaction method based on semantic web and intent recognition, which specifically includes the following steps:

[0062] Get FAQs in the industry as an interactive data source;

[0063] Semantically annotate the standard questions in the FAQs to build an industry semantic network;

[0064] Obtaining training corpus, the training corpus including the standard question, similar questions to the standard question, and intent labels corresponding to the standard question;

[0065] Training a machine learning model through the training corpus to obtain an intent recognition classification model;

[0066] Receiving a user question, performing intent recognition on the user question through the intent recognition classification model to obtain an intent candidate set, wherein the intent candidate set includes standard questions under several intent categories;

[0067] Based on the intent candidate set, perform multiple rounds of h...

Embodiment 2

[0166] image 3 A schematic structural diagram of an electronic device provided by Embodiment 2 of the present invention, such as image 3 As shown, the electronic device includes a processor 310, a memory 320, an input device 330, and an output device 340; the number of processors 310 in a computer device may be one or more, image 3 Take a processor 310 as an example; the processor 310, memory 320, input device 330 and output device 340 in the electronic device can be connected by bus or other methods, image 3 Take connection via bus as an example.

[0167] As a computer-readable storage medium, the memory 320 can be used to store software programs, computer-executable programs and modules, such as program instructions / modules corresponding to the human-computer interaction method based on semantic web and intent recognition in the embodiment of the present invention. The processor 310 executes various functional applications and data processing of the electronic device b...

Embodiment 3

[0171] Embodiment 3 of the present invention also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to implement a human-computer interaction method based on Semantic Web and intent recognition. The method includes:

[0172] Get FAQs in the industry as an interactive data source;

[0173] Semantically annotate the standard questions in the FAQs to build an industry semantic network;

[0174] Obtaining training corpus, the training corpus including the standard question, similar questions to the standard question, and intent labels corresponding to the standard question;

[0175] Training a machine learning model through the training corpus to obtain an intent recognition classification model;

[0176] Receiving a user question, performing intent recognition on the user question through the intent recognition classification model to obtain an intent candidate set, wherein ...

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PUM

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Abstract

The invention discloses a man-machine interaction method based on a semantic net and intention recognition, relates to the field of natural language processing, and aims to achieve accurate recognition of question intentions and improve the question and answer quality of man-machine interaction. The method comprises the following steps: obtaining common question answers in the industry as an interactive data source; performing semantic annotation on standard questions in the common question solutions, and constructing an industry semantic network; obtaining a training corpus; training an intention recognition classification model through the training corpus; and receiving a user question, performing intention recognition on the user question through the intention recognition classificationmodel to obtain an intention candidate set, performing multiple rounds of man-machine interaction through the industry semantic network based on the intention candidate set, determining a standard question matched with the intention of the user question, and outputting an answer. The invention further discloses electronic equipment and a computer storage medium.

Description

technical field [0001] The invention relates to the field of natural speech processing, in particular to a human-computer interaction method, device and medium based on semantic web and intention recognition. Background technique [0002] Personnel in call centers or customer service centers are generally highly mobile, which leads to high training costs for enterprises and a decline in customer service satisfaction, resulting in a substantial increase in operating costs. Therefore, more and more attention is paid to intelligent customer service. However, in the interaction process, intelligent customer service faces problems such as inaccurate recognition of intentions, vague intentions that cannot be located, and high maintenance costs for training corpus. [0003] In order to solve the above problems, in the prior art, there is a Chinese patent application 201710575327.5, which discloses a question answering method and device based on knowledge graphs, which acquire natur...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/35G06F40/211G06F40/242G06F40/289G06F40/35
CPCG06F16/3329G06F16/355G06F40/35G06F40/242G06F40/289G06F40/211
Inventor 嵇望钱艳王伟凯梁青安毫亿朱鹏飞陈默
Owner 杭州远传新业科技股份有限公司
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