• DocumentCode
    2366973
  • Title

    Machine Learning Trend Anticipation by Text Mining Methodology Based on SSCI Database

  • Author

    Chiang, Johannes K. ; Wu, Wen-Chin ; Liao, Wei-Cheng ; Yin, Chi-Yen

  • Author_Institution
    Dept. of Manage. Inf. Syst., Nat. Chengchi Univ., Taipei, Taiwan
  • fYear
    2009
  • fDate
    25-27 Aug. 2009
  • Firstpage
    612
  • Lastpage
    617
  • 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 auto-clustering", "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.
  • Keywords
    Internet; citation analysis; data mining; glossaries; learning (artificial intelligence); pattern clustering; text analysis; SSCI database; Social Science Citation Index; TF-IDF; Web 2.0; artificial intelligence; document pattern; financial domain; glossaries aggregation; homogeneous glossaries; information technology development; literature cluster analysis; machine learning trend anticipation; management application efficiency; text mining methodology; two step auto-clustering; Clustering algorithms; Clustering methods; Databases; Documentation; Machine learning; Management information systems; Technology management; Terminology; Text mining; Visualization; Machine Learnin; Text Mining; Two step auto-clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-5209-5
  • Electronic_ISBN
    978-0-7695-3769-6
  • Type

    conf

  • DOI
    10.1109/NCM.2009.382
  • Filename
    5331782