Learning-guiding question-answering system and method based on neural network

Abstract

The invention designs a learning-guiding question-answering system based on a neural network, which comprises a front end and a rear end, and is characterized in that the front end comprises a registration module, a login module, a questioning module, an answering module, an evaluation module and a cognitive evaluation tree module; the rear end comprises three subsystems, namely a cognitive evaluation subsystem, an answer reuse subsystem and an answer generation subsystem. According to the method, the answers of the existing questions in the community are retrieved by extracting the information of the questions; and if the similar questions do not exist, an answer is generated in the offline document by using the trained model, and the learner is guided to expanding reading in the returnedanswer.

Description

technical field [0001] The invention relates to a learning guidance question answering system and method based on neural network, belonging to the field of neural network and automatic question answering. Background technique [0002] Research in the fields of learning science and computer-assisted learning provides evidence that learners' dialogue is an important factor in their knowledge network construction. In offline teaching, classroom question and answer is a very important part of the traditional offline teaching mode. Therefore, the online question and answer technology in the online learning community restores the scene of offline teaching, providing learners and teachers with an online platform for interacting with learning partners. An environment that facilitates the flow of knowledge and the sharing of experiences between teachers and learners and between learners in the community. However, online question and answer lacks real-time performance. For example, i...

AI Technical Summary

Problems solved by technology

However, due to the continuous increase of learners in the online learning community, the questions raised by learners in the community cannot be answered by other users in a timely and accurate manner.

At the same time, due to the different descriptions of the questions by different learners, the same questions that already have answers cannot be fed back to the learners in time

However, only feeding back the answers to the questions to the learners can only make them accept the answers passively, but cannot make them actively expand reading, nor can it reflect the cognitive changes of learners participating in the discussion of the questions

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