| 基于语义感知的英文文献自动标引概念遴选方法 |
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| 引用本文： | 孟旭阳,白海燕,梁冰,王莉.基于语义感知的英文文献自动标引概念遴选方法[J].情报杂志,2021(3):125-131,7. |
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| 作者姓名： | 孟旭阳 白海燕 梁冰 王莉 |
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| 作者单位： | 中国科学技术信息研究所 |
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| 基金项目： | 中国科学技术信息研究所创新研究基金青年项目“基于语义感知的自动标引概念遴选优化研究”(编号:QN2020-14)的研究成果。 |
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| 摘 要： | 目的/意义]资源数字化时代文献服务向知识服务方向转变,高质量的文献自动标引是文献知识服务能力提升的基础和关键,针对目前英文科技文献自动标引准确率不高的问题,提出了基于语义感知的概念遴选优化方法。方法/过程]基于知识组织系统的自动主题标引,采用自然语言处理中的神经网络词向量技术,对概念和英文文献内容语义进行表示并进行语义感知与评估,实现概念标引结果在语义层面的遴选。该方法采用基于知识组织系统与自然语言处理技术相结合的方法,弥补了在语义层面上的不足,从而进一步降低不相关概念的影响,提高概念标引结果的准确率。结果/结论]实验结果表明,该方法具有较好的语义感知性能,在概念遴选上有效降低了不相关概念,大大提高了标引结果的文献相关性,为科技文献资源知识化服务建设和相关研究提供有价值的参考和支持。
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| 关 键 词： | 自动标引 概念遴选 语义感知 词向量技术 |
Automatic Indexing Concept Selection Method of English Documents Based on Semantic Perception |
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| Meng Xuyang,Bai Haiyan,Liang Bing,Wang Li.Automatic Indexing Concept Selection Method of English Documents Based on Semantic Perception[J].Journal of Information,2021(3):125-131,7. |
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| Authors: | Meng Xuyang Bai Haiyan Liang Bing Wang Li |
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| Institution: | (Institute of Scientific and Technical of Information of China,Beijing 100038) |
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| Abstract: | Purpose/Significance]In the era of resource digitalization,the literature service is changing to knowledge service.High-quality subject indexing is the foundation and key to improve the ability of literature knowledge services.Aiming at the low accuracy of automatic indexing of English scientific and technological literature,a concept selection optimization method based on semantic perception is proposed.Method/Process]Based on the automatic subject indexing of knowledge organization system,word embedding in natural language processing is used to represent the semantic vector of concept and literature content,and then perform semantic perception and evaluation to achieve the selection of concept indexing results at the semantic level.This method adopts a technical method based on the combination of knowledge organization system and natural language processing,which makes up for the lack of semantic level,further reduces the impact of unrelated concepts,and improves the accuracy of concept indexing results.Result/Conclusion]The experimental results show that the method in this paper has good semantic perception performance,effectively reduces irrelevant concepts,greatly improves the relevance of indexing results and literature,and provides valuable reference and support for the construction of scientific and technological literature resource knowledge service and related research. |
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| Keywords: | automatic indexing concept selection semantic perception word embedding |
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