Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/75046
題名: Machine learning trend anticipation by text mining methodology based on SSCI database
作者: Chiang, Johannes Kuo-huie;Liao, W.-C.
姜國輝
貢獻者: 資訊管理學系
關鍵詞: 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
日期: 2009
上傳時間: 7-五月-2015
摘要: 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.
關聯: NCM 2009 - 5th International Joint Conference on INC, IMS, and IDC,612-617
資料類型: conference
DOI: http://dx.doi.org/10.1109/NCM.2009.382
Appears in Collections:會議論文

Files in This Item:
File Description SizeFormat
index.html176 BHTML2View/Open
Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.