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Composition detecting and evaluating method based on user behavior

An evaluation method and behavioral technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as students' learning difficulties and different scores, and achieve the effect of improving composition learning efficiency.

Inactive Publication Date: 2018-10-26
校宝在线(杭州)科技股份有限公司
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Problems solved by technology

Manual evaluation requires specialized teachers or professionals. At the same time, manual repeated reading is required to give professional evaluations. Due to human subjective will, different personnel may have different scores. If the scores are different, it will be harmful to students. learning troubles

Method used

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Embodiment Construction

[0019] The present invention will be further described below in combination with specific embodiments.

[0020] A composition evaluation method based on user behavior, including a training stage and an evaluation stage. The training stage refers to: establishing a user behavior data set, and using deep learning technology to train the characteristics of organizational structure, difficulty of language expression, and diversity of language expression The scoring model extracts features according to the feature scoring model, and finally trains to obtain the composition scoring model; the evaluation stage refers to: collecting user behaviors from users, extracting the characteristics of organizational structure, difficulty of language expression, and diversity of language expression, and using composition Scoring model for composition evaluation.

[0021] Among them: the training phase steps are as follows:

[0022] (1) Establish a user behavior data set, record the past user b...

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Abstract

The invention discloses a composition detecting and evaluating method based on user behavior. The method includes a training stage and an evaluation stage. The training stage refers to: establishing auser behavior data set, using depth learning technology to train a feature scoring model of structured features, language expression difficulty features, language expression diversity features, extracting features according to the feature scoring model, and performing the final training to get a composition scoring model. The detecting and evaluating stage refers to: the collection of user behavior, the extraction of structured features, the difficulty of language expression, and the diversity of language expression, and the composition detecting and evaluating by using the composition scoring model. The invention has the beneficial effects that the user behavior analysis technology, the signal processing technology and the machine learning method are operated, the composition of the learner is accurately and automatically detected and evaluated, and the composition learning efficiency can be rapidly improved.

Description

technical field [0001] The present invention relates to the technical field related to machine learning, in particular to a composition evaluation method based on user behavior. Background technique [0002] With the improvement of people's living standards, people's enthusiasm for foreign language learning is increasing day by day. It is of great significance to study how to automatically evaluate compositions effectively and quickly. It can not only significantly reduce the workload of composition teachers, but also improve the efficiency of composition learning. At present, composition evaluation is mainly manual evaluation. Manual evaluation requires specialized teachers or professionals. At the same time, manual repeated reading is required to give professional evaluations. Due to human subjective will, different personnel may have different scores. If the scores are different, it will be harmful to students. learning troubles. With the development of modern science ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06N99/00
CPCG06F40/205
Inventor 蒋阳波
Owner 校宝在线(杭州)科技股份有限公司
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