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  • 标题:Data Mining in Sequential Pattern for Asynchronous Periodic Patterns
  • 本地全文:下载
  • 作者:Thodeti Srikanth
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2011
  • 卷号:8
  • 期号:6
  • 出版社:IJCSI Press
  • 摘要:Data Mining is becoming an increasingly important tool to transform enormous data into useful information. Mining periodic patterns in temporal dataset plays an important role in data mining and knowledge discovery tasks. This paper presents, design and development of software for sequential pattern mining for asynchronous periodic patterns in temporal database. Comparative study of various algorithms on sequential pattern mining for asynchronous periodic patterns is also carried out by taking artificial and real life database of glossary shop. The proposed system will be based on optimization of Efficient Mining of Asynchronous Periodic Pattern Algorithm (EMAP), which will be implemented for efficient mining of asynchronous periodic patterns in large temporal database.
  • 关键词:Sequential patterns; Temporal dataset; Knowledge discovery; Asynchronous Periodic patterns
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