Soft Computing for Data Mining Applications

  • K. R. Venugopal
  • K. G. Srinivasa
  • L. M. Patnaik

Part of the Studies in Computational Intelligence book series (SCI, volume 190)

Table of contents

  1. Front Matter
  2. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 1-17
  3. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 19-50
  4. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 51-62
  5. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 63-80
  6. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 81-118
  7. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 119-137
  8. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 139-166
  9. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 167-195
  10. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 197-215
  11. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 217-230
  12. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 231-247
  13. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 249-258
  14. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 259-278
  15. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 279-289
  16. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 291-301
  17. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 303-318
  18. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 319-330
  19. K. R. Venugopal, K. G. Srinivasa, L. M. Patnaik
    Pages 331-341

About this book

Introduction

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 fields of Data Mining in combination with Soft Computing methodologies. In these days, the data continues to grow exponentially. 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 stored is growing at a phenomenal rate. As a result, traditional ad hoc mixtures of statistical techniques and data management tools are no longer adequate for analyzing this vast collection of data. Several domains where large volumes of data are stored in centralized or distributed databases includes applications like in electronic commerce, bioinformatics, computer security, Web intelligence, intelligent learning database systems, finance, marketing, healthcare, telecommunications, and other fields.

With the importance of soft computing applied in data mining applications in recent years, this monograph gives a valuable research directions in the field of specialization. As the authors are well known writers in the field of Computer Science and Engineering, the book presents state of the art technology in data mining. The book is very useful to researchers in the field of data mining. - N R Shetty, President, ISTE, India

Keywords

Racter Web Intelligence algorithms bioinformatics data mining evolution genetic algorithm genome learning

Authors and affiliations

  • K. R. Venugopal
    • 1
  • K. G. Srinivasa
    • 2
  • L. M. Patnaik
    • 3
  1. 1.Bangalore UniversityIndia
  2. 2.M.S. Ramaiah Institute of TechnologyIndia
  3. 3.Defence Institute of Advanced TechnologyPuneIndia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-00193-2
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-00192-5
  • Online ISBN 978-3-642-00193-2
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book