Knowledge tracking method and system based on multivariate concept attention model

An attention model, attention technology, applied in the fields of educational data mining and knowledge tracking

Active Publication Date: 2021-09-10
ZHEJIANG GONGSHANG UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to address the deficiencies of the prior art, to provide a knowledge tracking method and system based on a multi-concept attention model, which can handle the exercises of multiple and complex concep...

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  • Knowledge tracking method and system based on multivariate concept attention model
  • Knowledge tracking method and system based on multivariate concept attention model
  • Knowledge tracking method and system based on multivariate concept attention model

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Embodiment Construction

[0068] In order to better understand the technical solutions of the present application, the embodiments of the present application will be described in detail below in conjunction with the accompanying drawings.

[0069] It should be clear that the described embodiments are only some of the embodiments of the present application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of this application.

[0070] Terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of this application and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise.

[0071] figure 1 The flow chart of the knowledge t...

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Abstract

The invention discloses a knowledge tracking method and system based on a multivariate concept attention model. The method comprises the following steps: acquiring an interaction sequence of historical exercise answers of a learner; establishing a multivariate concept attention model, and dividing an interaction sequence of historical exercise answers into a plurality of attention modules with different sizes according to the exercise key indexes of the learner; establishing a multivariate semantic attention model, and integrating the content of the context and attention module data; calculating the knowledge concept distribution weight of the to-be-tested exercise key index through the attention classification layer; multiplying the classified attention score value by the historical answer vector to obtain a feature score value of the learner answering the new exercise; and according to the feature score value and the to-be-tested exercise key index, calculating the probability that the learner correctly answers the current question, traversing historical exercises similar to the current knowledge state, and updating the knowledge state, thereby accurately constructing a learning route suitable for the learner.

Description

technical field [0001] The invention belongs to the field of educational data mining and knowledge tracking, and in particular relates to a knowledge tracking method and system based on a multi-concept attention model. Background technique [0002] With the rapid development of big data technology, data mining technology has also been introduced in the field of education. Especially with the rapid expansion of the Internet today, more and more people pay attention to and use online learning platforms. Knowledge tracking, as an important part of the online learning education system, has been the focus of numerous studies. According to the historical answer sequence of the learners, the knowledge points and concepts of the exercises are abstracted, and the knowledge tracking interactively models the learners and the exercises, and grasps the knowledge status of the learners in different periods, so as to predict their answers to the new exercises, so that Learners personaliz...

Claims

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Application Information

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IPC IPC(8): G06F40/30G06K9/62G06N3/04G06N3/08
CPCG06F40/30G06N3/08G06N3/045G06F18/2415Y02D10/00
Inventor 徐斌吴豪
Owner ZHEJIANG GONGSHANG UNIVERSITY
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