反馈文件质量
ia/softcomputingfor0000venu.pdf
Soft Computing for Data Mining Applications (Studies in Computational Intelligence, 190) 🔍
K. R. Venugopal; K.G. Srinivasa; L. M. Patnaik Berlin: Springer Verlag, Springer Nature, Berlin, Heidelberg, 2009
英语 [en] · PDF · 18.4MB · 2009 · 📗 未知类型的图书 · 🚀/duxiu/ia · Save
描述
The authors have consolidated their research work in this volume titled Soft Computing for Data Mining Applications. The monograph gives an insight into the research in the ?elds of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow - ponentially. Much of the data is implicitly or explicitly imprecise. Database discovery seeks to discover noteworthy, unrecognized associations between the data items in the existing database. The potential of discovery comes from the realization that alternate contexts may reveal additional valuable information. The rate at which the data is storedis growing at a phenomenal rate. Asaresult,traditionaladhocmixturesofstatisticaltechniquesanddata managementtools are no longer adequate for analyzing this vast collection of data. Severaldomainswherelargevolumesofdataarestoredincentralizedor distributeddatabasesincludesapplicationslikeinelectroniccommerce,bio- formatics, computer security, Web intelligence, intelligent learning database systems,?nance,marketing,healthcare,telecommunications,andother?elds. E?cient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the ca- bility of computers to search huge amounts of data in a fast and e?ective manner. However,the data to be analyzed is imprecise and a?icted with - certainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly con?icting. Besides, p- terns and relationships of interest are usually approximate. Thus, in order to make the information mining process more robust it requires tolerance toward imprecision, uncertainty and exceptions.
Erscheinungsdatum: 11.03.2009
备选作者
Venugopal, K. R., Srinivasa, K.G, Patnaik, L. M.
备选作者
Venugopal, K. R; Srinivasa, K. G; Patnaik, L. M
备选作者
K R Venugopal; K G Srinivasa; L M Patnaik
备用出版商
Spektrum Akademischer Verlag. in Springer-Verlag GmbH
备用出版商
Steinkopff. in Springer-Verlag GmbH
备用出版商
Springer Berlin
备用版本
Studies in computational intelligence -- v. 190, Studies in computational intelligence -- v. 190., Berlin, Germany, 2009
备用版本
Germany, Germany
备用版本
2009, PT, 2009
元数据中的注释
Includes bibliographical references.
备用描述
xxii, 341 p. : 24 cm
Includes bibliographical references
1. Introduction -- 2. Self Adaptive Genetic Algorithms -- 3. Characteristic Amplification Based Genetic Algorithms -- 4. Dynamic Association Rule Mining Using Genetic Algorithms -- 5. Evolutionary Approach for XML Data Mining -- 6. Soft Computing Based CBIR System -- 7. Fuzzy Based Neuro - Genetic Algorithm for Stock Market Prediction -- 8. Data Mining Based Query Processing Using Rough Sets and GAs -- 9. Hashing the Web for Better Reorganization -- 10. Algorithms for Web Personalization -- 11. Classifying Clustered Webpages for Effective Personalization -- 12. Mining Top - k Ranked Webpages Using SA and GA -- 13. A Semantic Approach for Mining Biological Databases -- 14. Probabilistic Approach for DNA Compression -- 15. Non-repetitive DNA Compression Using Memoization -- 16. Exploring Structurally Similar Protein Sequence Motifs -- 17. Matching Techniques in Genomic Sequences for Motif Searching -- 18. Merge Based Genetic Algorithm for Motif Discovery
开源日期
2024-07-01
更多信息……

🚀 快速下载

成为会员以支持书籍、论文等的长期保存。为了感谢您对我们的支持，您将获得高速下载权益。❤️
如果您在本月捐款，您将获得双倍的快速下载次数。

🐢 低速下载

由可信的合作方提供。 更多信息请参见常见问题解答。 （可能需要验证浏览器——无限次下载！）

所有选项下载的文件都相同，应该可以安全使用。即使这样，从互联网下载文件时始终要小心。例如，确保您的设备更新及时。
显示外部下载
  • 对于大文件，我们建议使用下载管理器以防止中断。
    推荐的下载管理器：JDownloader
  • 您将需要一个电子书或 PDF 阅读器来打开文件，具体取决于文件格式。
    推荐的电子书阅读器：Anna的档案在线查看器、ReadEra和Calibre
  • 使用在线工具进行格式转换。
    推荐的转换工具：CloudConvert和PrintFriendly
  • 您可以将 PDF 和 EPUB 文件发送到您的 Kindle 或 Kobo 电子阅读器。
    推荐的工具：亚马逊的“发送到 Kindle”和djazz 的“发送到 Kobo/Kindle”
  • 支持作者和图书馆
    ✍️ 如果您喜欢这个并且能够负担得起，请考虑购买原版，或直接支持作者。
    📚 如果您当地的图书馆有这本书，请考虑在那里免费借阅。