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    政大機構典藏 > 商學院 > 資訊管理學系 > 會議論文 >  Item 140.119/75046
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/75046


    Title: Machine learning trend anticipation by text mining methodology based on SSCI database
    Authors: Chiang, Johannes Kuo-huie;Liao, W.-C.
    姜國輝
    Contributors: 資訊管理學系
    Keywords: Machine-learning;Management applications;On-machines;Research domains;Social science citation indices;Text mining;Web 2.0;Artificial intelligence;Cluster analysis;Glossaries;Learning systems;Research;Semiconductor storage;Technological forecasting;Information management
    Date: 2009
    Issue Date: 2015-05-07 17:40:25 (UTC+8)
    Abstract: This paper is providing an introduction to the text mining methodology. There are many different researches which applying machine learning to improve its management application efficiency in various domains. This research is utilizing text mining technology, including "two step autoclustering", "glossaries aggregation", "TF-IDF" and so on, which collecting the homogeneous glossaries from articles, guiding to the literature cluster analysis based on the Social Science Citation Index (SSCI) database. The result discovered that the research domains of artificial intelligence, document pattern and financial related are the most prosperous fields on machine learning application, It is leading by information technology development progressing, web 2.0 is also a boost to research morale. All of these will become a power for important developing direction on machine learning in near future. © 2009 IEEE.
    Relation: NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC,612-617
    Data Type: conference
    DOI 連結: http://dx.doi.org/10.1109/NCM.2009.382
    DOI: 10.1109/NCM.2009.382
    Appears in Collections:[資訊管理學系] 會議論文

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