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[目的/意义]随着计算机信息处理技术以及文本数据挖掘技术的发展,研究人员开始利用语义分析技术深入分析科技文献文本数据,识别出科技文献中的科技创新内容,以期为科技创新和科技决策提供支持和帮助。[方法/过程]文章通过分析科技创新内容结构分布特征,以句子为最小标引粒度,利用Keygraph算法抽取出科技文献摘要中的关键词进行科技创新内容特征选择,基于SVM的语义角色标注技术完成科技创新内容的语义表征。[结果/结论]实验结果表明,语义增强的科技创新表征方法可以基本实现科技创新内容的语义标引。
[Purpose / Significance] With the development of computer information processing and text data mining technologies, researchers began to use semantic analysis technology to deeply analyze the text data of scientific literature and to identify the content of scientific and technological innovation in scientific literature so as to make scientific and technological innovation and technological decision-making Provide support and help. [Methods / Processes] By analyzing the distribution characteristics of content structure of science and technology innovation, taking the sentence as the minimum index granularity, this paper uses Keygraph algorithm to extract key words from scientific and technological literature abstracts to select the features of scientific and technological innovation content, and completes the semantic role labeling technology based on SVM Semantic Representation of Content of Science and Technology Innovation. [Result / Conclusion] The experimental results show that the semantic-enhanced scientific and technological innovation and characterization method can basically realize the semantic indexing of scientific and technological innovation content.