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  • 标题:TEXT MINING: ADVANCEMENTS, CHALLENGES AND FUTURE DIRECTIONS
  • 本地全文:下载
  • 作者:MAHESH T R ; SURESH M B ; M VINAYABABU
  • 期刊名称:International Journal of Reviews in Computing
  • 印刷版ISSN:2076-3328
  • 电子版ISSN:2076-3336
  • 出版年度:2010
  • 卷号:3
  • 出版社:Little Lion Scientific Research and Developement
  • 摘要:Text mining, also known as text data mining or knowledge discovery from textual databases, refers to the process of extracting interesting and non-trivial patterns or knowledge from text documents. Regarded by many as the next wave of knowledge discovery, text mining has very high commercial values. Last count reveals that there are more than ten high-tech companies offering products for text mining. Has text mining evolved so rapidly to become a mature field? This article attempts to shed some lights to the question. We first present a text mining framework consisting of two components: Text refining that transforms unstructured text documents into an intermediate form; and knowledge distillation that deduces patterns or knowledge from the intermediate form. We then survey the state-of-the-art text mining products/applications and align them based on the text refining and knowledge distillation functions as well as the intermediate form that they adopt. In conclusion, we highlight the upcoming challenges of text mining and the opportunities it offers.
  • 关键词:Text Mining; Data Mining; Knowledge Discovery
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