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  • 标题:Role of soft computing as a tool in data mining
  • 本地全文:下载
  • 作者:Kanhaiya Lal ; N.C.Mahanti
  • 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:1
  • 页码:526-537
  • 出版社:TechScience Publications
  • 摘要:we live in a world where we can be overwhelmed with information; therefore it has become increasingly important to extract relevant information from the explosive amount of data for. Data Mining is the iterative and interactive process of discovering valid, novel, useful, and understandable patterns or models in massive databases. Data Mining means searching for valuable information in large volumes of data, using exploration and analysis, by automatic or semi-automatic means, of large quantities of data in order to discover meaningful patterns and rules. With an enormous amount of data stored in databases and data warehouses develop powerful tools for analysis. Soft computing, are used to identify relationships among a set of items in a database. These relationships are not based on inherent properties of the data themselves (as with functional dependencies), but rather based on cooccurrence of the data items. In this process we discover a set of association rules at multiple levels of abstraction from the relevant set(s) of data in a database. A fundamental challenge is to extend data mining to large data sets. In addition to sharing and applying the knowledge in the community, knowledge discovery has become an important issue in the knowledge economic era. Data mining plays an important role of knowledge discovery. Therefore, this study intends to propose a novel framework of data mining which clusters the data first and then followed by association rules mining. Soft computing is being used as the important tool in this area. The main constitutes of soft computing include fuzzy logic, neural networks, genetic algorithms and rough sets. Each of them contributes a distinct methodology for addressing problems in its domain. This is done in a cooperative, rather than a competitive, manner. The result is a more intelligent and robust system providing a humaninterpretable, low-cost, approximate solution, as compared to traditional techniques. This is a review of the role of various soft-computing tools for different data mining tasks
  • 关键词:fuzzy logic; neural networks; genetic;algorithms; rough sets; association rule; clustering.
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