Machine Learning on language style

被引:0
|
作者
Wang, Yufeng [1 ]
Wang, Zhiliang [1 ]
Lu, Xiaojuan [1 ]
Chen, Liang [1 ]
Zhao, Jian [1 ]
Che, Lingling [1 ]
Zai, Ying [1 ]
Wang, Lijuan [1 ]
机构
[1] Univ Sci & Technol Beijing, Informat Sch, Dept Elect & Informat, Beijing 100083, Peoples R China
来源
CMESM 2006: Proceedings of the 1st International Conference on Enhancement and Promotion of Computational Methods in Engineering Science and Mechanics | 2006年
关键词
Machine Learning; Natural Language Processing; artificial psychology; affective computing;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
To find out the method of Language Style Machine Learning, established a natural language communication model with Abstract Algebra. Analyze the relations on the model. Note the Universal Property of free semigroups for Word Monoids. Conclude by a practical example that the word class and the word order are two stable elements during language transferring. Because that the word class and the word order are two parts of phrase structure, the phrase structure is the feature of language style. We can apply Natural Language Processing method to get the feature of language style, automatically by phrase structure identification and phrase structure probabilities counting. Thus establish a foundation for further Machine Learning.
引用
收藏
页码:380 / 382
页数:3
相关论文
共 50 条
  • [41] Sign Language Recognition Using Machine Learning
    Soundarya, M.
    Yazhini, M.
    Sree, Thirumala N. S.
    Sornamalaya, N. M.
    Vinitha, C.
    2024 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND APPLIED INFORMATICS, ACCAI 2024, 2024,
  • [42] Knowledgeable Machine Learning for Natural Language Processing
    Han, Xu
    Zhang, Zhengyan
    Liu, Zhiyuan
    COMMUNICATIONS OF THE ACM, 2021, 64 (11) : 50 - 51
  • [43] A Meta-Language Approach for Machine Learning
    Caporusso, Nicholas
    Helms, Trent
    Zhang, Peng
    ADVANCES IN ARTIFICIAL INTELLIGENCE, SOFTWARE AND SYSTEMS ENGINEERING, 2020, 965 : 192 - 201
  • [44] Indigenous language technology in the age of machine learning
    Moshagen, Sjur Norstebo
    Antonsen, Lene
    Wiechetek, Linda
    Trosterud, Trond
    ACTA BOREALIA, 2024, 41 (02) : 102 - 116
  • [45] MACHINE LEARNING OF NATURAL-LANGUAGE AND ONTOLOGY
    POWERS, DMW
    REEKER, LH
    IEEE EXPERT-INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 1991, 6 (06): : 62 - 63
  • [46] Machine learning in statistical natural language processing
    Mochihashi, Daichi
    Kyokai Joho Imeji Zasshi/Journal of the Institute of Image Information and Television Engineers, 2015, 69 (02): : 131 - 135
  • [47] AN ADAPTIVE PROLOG PROGRAMMING LANGUAGE WITH MACHINE LEARNING
    Lu, Benjie
    Liu, Zhiqing
    Gao, Hui
    2012 IEEE 2ND INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENT SYSTEMS (CCIS) VOLS 1-3, 2012, : 21 - 24
  • [48] Sign Language Detection Using Machine Learning
    Ilanchezhian, P.
    Singh, I. Amit Kumar
    Balaji, M.
    Kumar, A. Manoj
    Yaseen, S. Muhamad
    SEMANTIC INTELLIGENCE, ISIC 2022, 2023, 964 : 135 - 143
  • [49] Applying machine learning to language problem analysis
    Chu, Kuo-Chung
    Chiu, Yu-Jen
    Masud, Jakir Hossain Bhuiyan
    2024 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION FOR DATA SCIENCE, IRI 2024, 2024, : 200 - 203
  • [50] Style classification and prediction of residential buildings based on machine learning
    Xia, Bing
    Li, Xin
    Shi, Hui
    Chen, Sichong
    Chen, Jiamei
    JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING, 2020, 19 (06) : 714 - 730