[目的/意义] 为了促进主题词表的应用，发挥其在数智时代的知识组织功能，开展相关测试与分析研究。[方法/过程] 使用在线《汉语主题词表》服务系统，对部分工程技术科技文献和《红楼梦》文本进行自动标引和主题聚类测试与分析，分别对两种不同类型的文献，分析对比分词、标引和主题聚类效果，并进行可视化对比分析。[结果/结论] 《汉语主题词表》服务系统可以很好地标引出领域相关知识主题，知识组织具有领域特征；对于主题词表没有涵盖的专业知识，标引功能受限甚至有误，但仍可以开发新的知识组织应用。
[Purpose/Significance] In order to promote the application of thesauri and develop their knowledge organization function in the digital age, this paper conducts related testing and analysis. [Method/Process] Using the online Chinese Thesaurus Service System, automatic indexing and topic clustering analysis tests were performed on some selected engineering and technological literature and the text of “Dream of the Red Mansions”. The word segmentation, indexing, and topic clustering effects of two different types of literature were analyzed and compared, and a visualized comparative analysis was conducted. [Result/Conclusion] The “Chinese Thesaurus” service system can effectively index topics related to domain knowledge, and its knowledge organization has domain characteristics. The indexing function is limited or even incorrect for specialized knowledge not covered by the thesaurus, new knowledge organization applications can still be developed.
[1] 中国科学技术信息研究所. 《汉语主题词表》服务系统[EB/OL]. [2025-04-07]. https://ct.istic.ac.cn. (Institute of Scientific and Technical Information of China. Chinese thesaurus service system[EB/OL]. [2025-04-07]. https://ct.istic.ac.cn)
[2] 中国科学技术情报研究所, 北京图书馆. 汉语主题词表[M]. 北京: 科学技术文献出版社, 1980. (Institute of Scientific and Technical Information of China, Beijing Library. Chinese thesaurus[M]. Beijing: Scientific and Technical Documentation Press, 1980.)
[3] 中国科学技术情报研究所. 汉语主题词表（自然科学增订本）[M]. 北京: 科学技术文献出版社, 1991. (Institute of Scientific and Technical Information of China. Chinese thesaurus (natural science revised edition) [M]. Beijing: Scientific and Technical Documentation Press, 1991.)
[4] 中国科学技术信息研究所. 汉语主题词表（工程技术卷）[M]. 北京: 科学技术文献出版社, 2014. (Institute of Scientific and Technical Information of China. Chinese thesaurus (engineering technology volume) [M]. Beijing: Scientific and Technical Documentation Press, 2014.)
[5] 中国科学技术信息研究所. 汉语主题词表（自然科学卷）[M]. 北京: 科学技术文献出版社, 2018. (Institute of Scientific and Technical Information of China. Chinese thesaurus (natural science volume) [M]. Beijing: Scientific and Technical Documentation Press, 2018.)
[6] 中华人民共和国科学技术部. 科技部关于发布科技基础资源调查专项2019年度项目指南的通知[EB/OL]. [2025-04-07]. https://www.gov.cn/zhengce/zhengceku/2019-12/03/content_5457766.htm. (Ministry of Science and Technology of the Peoplés Republic of China. Notice from the Ministry of Science and Technology on the release of the 2019 project guidelines for the special investigation of science and technology basic resources[EB/OL]. [2025-04-07]. https://www.gov.cn/zhengce/zhengceku/2019-12/03/content_5457766.htm.)
[7] 杨小平, 马奇凤, 余力, 等. 评论簇在网络舆论中的情感倾向代表性研究[J]. 现代图书情报技术, 2016(7): 51-59. (YANG X P, MA Q F, YU L, et al. Gauging public opinion with comment-clusters[J]. Modern library and information technology, 2016(7): 51-59.)
[8] 尤众喜, 华薇娜, 潘雪莲. 中文分词器对图书评论和情感词典匹配程度的影响[J]. 数据分析与知识发现, 2019, 3(7): 23-33. (YOU Z X, HUA W N, PAN X L. M. Matching book reviews and essential sentiment lexicons with Chinese word segmenters[J]. Data analysis and knowledge discovery, 2019, 3(7): 23-33.)
[9] 李湘东, 高凡, 李悠海. 共通语义空间下的跨文献类型文本自动分类研究[J]. 数据分析与知识发现, 2018, 2(9): 66-73. (LI X D, GAO F, LI Y H. Categorizing documents automatically within common semantic space[J]. Data analysis and knowledge discovery, 2018, 2(9): 66-73.)
[10] 廖春林, 张宏军, 廖湘琳, 等. 开源自然语言处理工具综述[J]. 计算机工程与应用, 2023, 59(22): 36-56. (LIAO C L, ZHANG H J, LIAO X L, et al. Survey of open source natural language processing tools[J]. Computer engineering and applications, 2023, 59(22): 36-56.)
[11] 侯汉清, 薛春香. 用于中文信息自动分类的《中图法》知识库的构建[J]. 中国索引, 2005(3): 31-36. (HOU H Q, XUE C X. Construction of the knowledge base for automatic classification of Chinese information in Chinese Library Classification[J]. Journal of the China society of indexers, 2005(3): 31-36.)
[12] 王莉, 许凯. 浅谈文本数据自动标引系统的设计[J]. 图书馆理论与实践, 2013(6): 95-97. (WANG L, XU K. Design of automatic indexing system of text data[J]. Library theory and practice, 2013(6): 95-97.)
[13] 常春. 基于《汉语主题词表》的自动标引测试与分析[C]//第六届全国文献编目工作研讨会论文集. 北京: 国家图书馆出版社, 2020: 1-8. (CHANG C. Automatic indexing testing and analysis based on the Chinese Thesaurus[C]//Proceedings of the 6th national symposium on document cataloging work. Beijing: National Library Press, 2020:1-8.)
[14] 刘竟, 李寻珣, 刘桂锋, 等. 学科演变视角下图书馆学概念知识元的识别[J]. 图书馆论坛, 2024, 44(3): 71-79. (LIU J, LI X X, LIU G F, et al. Research on the recognition of library science conceptual knowledge elements based on disciplinary evolution[J]. Library tribune, 2024, 44(3): 71-79.)
[15] 白硕, 苗亚敏, 李晓敏, 等. 我国“互联网+”慢性病管理模式的研究热点及前沿分析[J]. 中国社会医学杂志, 2023, 40(5): 511-514. (BAI S, MIAO Y M, LI X M, et al. Research hotspots and frontier analysis of “internet plus” chronic disease management model in China[J]. Chinese journal of social medicine, 2023, 40(5): 511-514.)
[16] 金悦. 文化科技融合视角下我国公共数字文化服务政策主题变迁与文本量化研究[D]. 南昌: 南昌大学, 2023. (JIN Y. Research on policy theme change and text quantification of public digital cultural service in China from the perspective of integration of culture and science [D]. Nanchang: Nanchang University, 2023.)
[17] 刘爱琴, 马小宁. 基于概率主题模型的短文本自动分类系统构建[J]. 国家图书馆学刊, 2020, 29(6): 102-112. (LIU A Q, MA X N. Establishment of short text automatic classification system based on probability subject model[J]. Journal of the National Library of China, 2020, 29(6): 102-112.)
[18] 王阳阳. 基于朴素贝叶斯与BP网络神经分类方法的《红楼梦》文本特征差异研究[J]. 统计与决策, 2018, 34(13): 121-125. (WANG Y Y. Research on the differences in text features of Dream of Red Mansions based on naive bayes and BP neural network classification method[J]. Statistics & decision, 2018, 34(13): 121-125.)
[19] 曹雪芹. 红楼梦[M]. 无名氏, 续. 程伟元, 高鹗, 整理. 3版. 北京: 人民文学出版社, 2008. (CAO X Q. Dream of Red Mansions[M]. Anonymity, extend. CHENG W Y, GAO E, collate. 3rd ed. Beijing: People’s Literature Publishing House, 2008.)
[20] 常利伟, 程磊, 陈进, 等. 水库和大坝地理信息数据集的对比及其应用研究进展[J]. 中国农村水利水电, 2023(6): 1-11, 20. (CHANG L W, CHENG L, CHEN J, et al. Comparison and application of georeferenced reservoir and dam data sets[J]. China rural water and hydropower, 2023(6): 1-11, 20.)
