Target field question and answer pushing method combining keyword retrieval and twin neural network

A target field and neural network technology, applied in the field of question and answer push in the target field combined with keyword retrieval and twin neural network, can solve problems such as difficulty in ensuring real-time performance of the system, large amount of calculation, etc.

Active Publication Date: 2019-07-23
浙江爱闻格环保科技有限公司
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Problems solved by technology

However, due to the need to calculate the semantic similarity between user questions and each historical question (or historical answer), the

Method used

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  • Target field question and answer pushing method combining keyword retrieval and twin neural network
  • Target field question and answer pushing method combining keyword retrieval and twin neural network
  • Target field question and answer pushing method combining keyword retrieval and twin neural network

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Embodiment Construction

[0050] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0051] On the contrary, the invention covers any alternatives, modifications, equivalent methods and schemes within the spirit and scope of the invention as defined by the claims. Further, in order to make the public have a better understanding of the present invention, some specific details are described in detail in the detailed description of the present invention below. The present invention can be fully understood by those skilled in the art without the description of these detailed parts.

[0052] like figure 1 As shown, a method of pushing answers to questions in a target domain that combi...

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Abstract

The invention discloses a target field question and answer pushing method combining keyword retrieval and a twin neural network. According to the method, the historical questions are preprocessed based on the Internet and the expert knowledge, and then an answer with the highest matching degree is intelligently pushed to a real-time question proposed by a user in combination with a keyword retrieval method and a semantic similarity model based on the twin neural network. According to the method, the efficiency and the performance can be better balanced, meanwhile, the recall rate and the accuracy of the method are guaranteed, and the method has great practical significance in the field of intelligent question and answer systems.

Description

technical field [0001] The invention relates to the fields of data mining and natural language processing, in particular to a method for pushing questions and answers in a target field combining keyword retrieval and a twin neural network. Background technique [0002] Similar to the search engine system, the intelligent question answering system also finds the text information that best meets the user's intention from a large amount of data. However, the differences between the two include: First, the search engine system requires users to explicitly input keywords, while the intelligent question answering system allows users to input free questions that are more in line with human habits. Secondly, the search engine system returns a large number of search results, and users need to find the one that best meets their intentions, while the intelligent question answering system returns one or a small number of results that best meet the user's intentions, which can greatly im...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/335G06N3/04G06N3/08
CPCG06F16/3329G06F16/335G06N3/08G06N3/045
Inventor 安军张维碟庄铭权王琦晖吕明琪金永平张曼怡顾昀晖
Owner 浙江爱闻格环保科技有限公司
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