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  • 标题:Efficient Apriori Mend Algorithm for Pattern Extraction Process
  • 本地全文:下载
  • 作者:D.Magdalene Delighta Angeline ; I.Samuel Peter James
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2011
  • 卷号:2
  • 期号:6
  • 页码:2788-2791
  • 出版社:TechScience Publications
  • 摘要:Association rules reflect the inner relationship of data. Discovering these associations is beneficial to the correct and appropriate decision made by decision-makers. The association rules provide an effective means to found the potential link between the data, reflecting a built-in association between the data. In this paper, we make an indepth the study of the mining association rules for Student’s placement in industry. Student’s placement for the practicum training is difficult due to the large number of students and organizations involved. Further the matching process is complex due to the various criteria set by the organization and students. This paper will discuss the results of a pattern extraction process using association rules of data mining technique using Apriori Mend algorithm.
  • 关键词:Apriori Mend Algorithm; Association rules;Data mining; Knowledge Discoveryorks
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