| 基于关联矩阵的短信自动分类 |
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| 引用本文： | 李锋,万小强.基于关联矩阵的短信自动分类[J].计算机科学,2017,44(Z6):428-432. |
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| 作者姓名： | 李锋 万小强 |
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| 作者单位： | 东华大学计算机科学与技术学院 上海200000,东华大学计算机科学与技术学院 上海200000 |
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| 基金项目： | 本文受上海市自然基金项目(16ZR1401100)资助 |
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| 摘 要： | 短信自动分类是短文本研究的热点问题。针对此问题,提出了关联强度和关联矩阵特征提取方法,并设计了基于关联矩阵的全监督学习算法。为了实现系统的自我学习,探讨了基于关联矩阵的半监督学习算法,其结合了人工矫正的主动学习算法。最后通过实例验证说明了算法的有效性。
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| 关 键 词： | 短文本 短信自动分类 关联矩阵 半监督学习 主动学习 |
SMS Automatic Classification Based on Relational Matrix |
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| LI Feng and WAN Xiao-qiang.SMS Automatic Classification Based on Relational Matrix[J].Computer Science,2017,44(Z6):428-432. |
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| Authors: | LI Feng and WAN Xiao-qiang |
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| Affiliation: | College of Computer Science and Technology,Donghua University,Shanghai 200000,China and College of Computer Science and Technology,Donghua University,Shanghai 200000,China |
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| Abstract: | SMS automatic classification is a hot issue of short text study.In this problem,this paper put forward to the feature extraction method of relational strength and the relational matrix,and designed a fully supervised learning algorithm based on relational matrix.In order to implement the system of self learning,this paper also discussed a semi-supervised learning algorithm based on relational matrix,which combines with active learning algorithm of the artificial modification.Finally the experiment results illustrate the effectiveness and efficiency of this algorithm. |
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| Keywords: | Short text SMS automatic classification Relational matrix Semi-supervised learning Active learning |
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