计算机科学 ›› 2016, Vol. 43 ›› Issue (3): 279-284.doi: 10.11896/j.issn.1002-137X.2016.03.052
温浩,温有奎,王民
WEN Hao, WEN You-kui and WANG Min
摘要： 针对目前大数据知识获取存在的噪声大的问题,提出了文本知识点深度挖掘方法。首先构建了学术论文创造性特征的“问题,方法,结果”三元组本体模型；其次利用模式识别等技术对学术论文文摘进行统计分析、特征提取、机器学习、模式判定分析；最后对学术论文创造性核心知识的三元组进行深度挖掘。实验结果表明,该方法能大大过滤掉学术文献大数据检索的噪声,便于用户快速定位大型学术文献数据库论文的研究问题,采用的新方法和得到的结果能判断学术论文的阅读价值,并为大数据深度知识挖掘和关联发现研究提供基础。该类方法未见有公开的文献报道,属于一种探索性研究和实验。
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