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A Method of K-Means Clustering Based on TF-IDF for Software Requirements Documents Written in Chinese Language

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成果类型:
期刊论文
作者:
Zhu, Jing;Huang, Song;Shi, Yaqing;Wu, Kaishun;Wang, Yanqiu
通讯作者:
Zhu, J
作者机构:
[Shi, Yaqing; Huang, Song; Wu, Kaishun; Zhu, Jing] Army Engn Univ PLA, Command & Control Engn Coll, Nanjing 210000, Peoples R China.
[Zhu, Jing] Navy Command Coll, Training Management Dept, Nanjing 210000, Peoples R China.
[Wang, Yanqiu] Baopo Technol Co Ltd, Nanjing 210000, Peoples R China.
通讯机构:
[Zhu, J ] A
Army Engn Univ PLA, Command & Control Engn Coll, Nanjing 210000, Peoples R China.
Navy Command Coll, Training Management Dept, Nanjing 210000, Peoples R China.
语种:
英文
关键词:
Chinese;clustering;K-means;TF-IDF
期刊:
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
ISSN:
1745-1361
年:
2022
卷:
105
期:
4
页码:
736-754
基金类别:
National Key R&D Program of China [2018YFB1403400]; Natural Science Foundation of China [61702544]; Natural Science Foundation of Jiangsu Province, China [BK20141072, BK20160769]; China Postdoctoral Science Foundation [2016M603031]
机构署名:
本校为通讯机构
摘要:
Nowadays there is no way to automatically obtain the function points when using function point analyze (FPA) method, especially for the requirement documents written in Chinese language. Considering the characteristics of Chinese grammar in words segmentation, it is necessary to divide words accurately Chinese words, so that the subsequent entity recognition and disambiguation can be carried out in a smaller range, which lays a solid foundation for the efficient automatic extraction of the function points. Therefore, this paper proposed a metho...

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