Knowledge point predicting method and device, storage medium and electronic device

A prediction method and knowledge point technology, which can be used in prediction, digital data processing, semantic analysis, etc., and can solve problems such as low prediction accuracy.

Active Publication Date: 2018-04-27
IFLYTEK CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Currently commonly used machine learning methods include traditional machine learning methods

Method used

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  • Knowledge point predicting method and device, storage medium and electronic device
  • Knowledge point predicting method and device, storage medium and electronic device
  • Knowledge point predicting method and device, storage medium and electronic device

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Embodiment Construction

[0072] Specific embodiments of the present disclosure will be described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to illustrate and explain the present disclosure, and are not intended to limit the present disclosure.

[0073] see figure 1 , shows a schematic flowchart of the knowledge point prediction method of the present disclosure. The pre-built knowledge point prediction model can be used to determine the test questions q to be predicted t Contained knowledge points, including the following steps:

[0074] S101, extracting the test question q to be predicted t Deep Semantic Information QD qt .

[0075] In the disclosed scheme, the knowledge point prediction model can extract the test questions q to be predicted through deep semantic analysis t Semantic information in terms of words, word context, sentence word order, or discourse structure.

[0076] As an example...

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Abstract

The invention provides a knowledge point predicting method and device, a storage medium and an electronic device. The method determines knowledge points contained by a to-be-predicted test question qtthrough a pre-established knowledge predicting model, and includes the steps of extracting deep semantic information QDqt of the to-be-predicted test question qt and deep semantic information JDkj ofteaching and research experience of each knowledge point kj in a knowledge point set, wherein the teaching and research experience of each knowledge point is the description of the knowledge point inthe test question, j is larger than or equal to 1 and smaller than or equal to m, and m is the number of the knowledge points contained by the knowledge point set; obtaining the similarity Wqtkj between the QDqt and the JDkj through an attention mehcanims, and obtaining the importance degree Cqt of the teaching and research experience for the to-be-predicted test question qt based on the QDqt andthe JDkj; predicting the knowledge points contained by the to-be-predicted test question qt through the QDqt and the Cqt. By means of the scheme, the knowledge point predicting accuracy can be easilyimproved.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, and in particular, to a knowledge point prediction method and device, a storage medium, and electronic equipment. Background technique [0002] With the development of big data and artificial intelligence, the personalized learning mode has been widely used. It can provide students with personalized diagnosis reports and personalized resource recommendations, help students understand themselves, and use big data and artificial intelligence to plan personalized learning for students. Learning paths, recommending personalized learning resources, making learning simple and efficient. [0003] In the personalized learning mode, whether it is the generation of personalized diagnostic reports or the recommendation of personalized resources, an effective method is to construct a structured question bank from the dimension of knowledge points, and then combine the learning histor...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06Q10/04G06Q50/20
CPCG06Q10/04G06Q50/205G06F40/205G06F40/289G06F40/30
Inventor 张丹苏喻李佳高明勇刘青文王瑞胡国平
Owner IFLYTEK CO LTD
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