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Subjective question marking system and method combining short text clustering and recommendation mechanism

A technology of subjective questions and short texts, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve problems such as the inability to apply the automatic review system, the low reliability of the review data, and the inability to trace the review process, etc., to achieve The effect of reducing random reviews, avoiding the possibility of inconsistency, and reducing accidental errors

Active Publication Date: 2018-11-06
BEIJING NORMAL UNIVERSITY
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Problems solved by technology

[0003] The technical problem to be solved by the present invention is to overcome the problems encountered in the current acquisition of subjective test review data: the current review data has low reliability and poor consistency, the review process cannot be traced back, and cannot be applied to training subjective test automatic review system, etc., to promote the fairness of the examination

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  • Subjective question marking system and method combining short text clustering and recommendation mechanism
  • Subjective question marking system and method combining short text clustering and recommendation mechanism
  • Subjective question marking system and method combining short text clustering and recommendation mechanism

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Embodiment Construction

[0030] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0031] Such as figure 1 As shown, the present invention includes that the system includes a computer and an answering interface marked with specific segmentation symbols; the computer runs a subjective question review system, and the review system includes a data preprocessing module, a cluster analysis module, a recommendation visualization module, Approved database.

[0032] Such as figure 2 As shown, the specific implementation of the data preprocessing module in the present invention is as follows:

[0033] The user submits the students' answers, and uploads the answers to the review database. In this embodiment, the open source word segmentation tool jieba (see: ) can also be used to opennlp (http: / / opennlp.apache.org / ) or nlpir (http: / / ictclas. nlpir.org / ) and the built custom user dictionary to segment the answer, jieba is a common...

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Abstract

A subjective question marking system and method combining short text clustering and recommendation mechanism are disclosed. The system comprises a computer. The computer runs a subjective question marking system, and the marking system comprises a data preprocessing module, a clustering analysis module, a recommendation visualization module and a marking database. The invention is suitable for obtaining the marking data of the subjective questions, and is characterized in that the short text clustering and the recommendation mechanism are applied to the marking scene, thereby obtaining the marking result with higher reliability and stronger consistency; on the one hand, the problem that the credibility of the training automatic marking model is not high due to poor marking consistency canbe solved. On the other hand, the credibility of user marking behavior is improved, the score scale changes in the marking process are reduced, and the fairness of marking results is increased.

Description

technical field [0001] The invention belongs to the field of review data collection, specifically, a subjective question review system and method combined with short text clustering and recommendation mechanisms, the system can be applied to subjective question review and high-quality subjective question review data in primary and secondary schools Obtain. Background technique [0002] Subjective question review is an important part of students' learning and teaching, and it is an important way for teachers to understand students' knowledge mastery. At present, teacher review is also a very important step to realize automatic machine review. The current homework review method is single, mainly full-batch full-reform and intensive-batch fine-tune (Yu Taimeng. From "full batch full-reform" to "fine-batch and ingenious correction"[J]. Friends of Students (Junior High School Edition), 2011,09 :14.), homework platforms developed for this method are also emerging, such as homewor...

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Application Information

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IPC IPC(8): G06F17/30G06F17/27G06Q50/20
CPCG06Q50/205G06F40/242G06F40/289G06F40/30
Inventor 余胜泉段庆龙卢宇
Owner BEIJING NORMAL UNIVERSITY
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