基于OM/QM智能阅卷系统的主题纠错分析

Zhuming Nie, Ying Wang, Yuhan Shi
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引用次数: 0

摘要

智能打标技术具有高效率、高精度、高可靠性等特点,可以有效改善和解决在线人工打标存在的问题。但是,主观题智能阅卷在技术、流程、功能、安全性等方面还存在许多问题,亟待改进。本研究在获得主观题智能阅卷的第一手资料的同时,深入挖掘和调查了与智能阅卷相关的案例和人员,并针对具体问题提出了相应的建议。个人问题亮点标注存在的问题:文本识别准确率不足,识别模型训练过程复杂;哲学算法逻辑复杂,难以“覆盖”,数据不可追溯;智能打标模型单一,缺乏复制机制。针对这三个问题,提出了以下解决方案:基于检测-识别纠错机制的文本识别模型;基于文本聚类分析的智能样本选择机制基于人工打标与机器打标融合的智能打标新模式。
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Analysis of Subjective Question Correction Based on OM/QM Intelligent Marking System
The intelligent marking technology can effectively improve and solve the problems existing in online manual marking due to its high efficiency, high accuracy, and high reliability. However, there are still many problems in the technology, process, function, and safety of intelligent marking of subjective questions, which need to be improved urgently. This research deeply excavates and investigates the cases and personnel related to bright marking and puts forward corresponding suggestions based on specific problems while obtaining first-hand information on intelligent marking of subjective questions. Existing issues in brilliancy marking of personal questions: insufficient text recognition accuracy, complex recognition model training process; philosophical algorithm logic are complicated to “override”, and data are not traceable; the intelligent marking model is single, lacking a replication mechanism. Based on three problems, the following solutions are proposed: text recognition model based on detection-recognition correction mechanism; intelligent sample selection mechanism based on text clustering analysis; new smart marking mode based on the fusion of manual marking and machine marking.
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