LEADER 03271oam 2200613I 450 001 9910809843503321 005 20230721022326.0 010 $a0-367-38555-4 010 $a0-429-11670-5 010 $a1-282-11123-X 010 $a9786612111235 010 $a1-4200-4591-1 024 7 $a10.1201/9781420045918 035 $a(CKB)1000000000786659 035 $a(EBL)1446804 035 $a(SSID)ssj0000137153 035 $a(PQKBManifestationID)11130039 035 $a(PQKBTitleCode)TC0000137153 035 $a(PQKBWorkID)10087974 035 $a(PQKB)11606687 035 $a(MiAaPQ)EBC1446804 035 $a(Au-PeEL)EBL1446804 035 $a(CaPaEBR)ebr11004070 035 $a(CaONFJC)MIL211123 035 $a(OCoLC)899156214 035 $a(OCoLC)431939964 035 $a(EXLCZ)991000000000786659 100 $a20180331d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aDesign and implementation of data mining tools /$fM. Awad. [et al.] 210 1$aBoca Raton, Fla. :$cAuerbach Publications,$d2009. 215 $a1 online resource (276 p.) 300 $a"An Auerbach book." 311 $a1-4665-2603-3 311 $a1-4200-4590-3 320 $aIncludes bibliographical references and index. 327 $aFront cover; Dedication; Contents; Preface; About the Authors; Acknowledgments; Chapter 1. Introduction; Chapter 2. Data Mining Techniques; Chapter 3. Data Mining Applications; Chapter 4. Data Mining for Security Applications; Chapter 5. Dynamic Growing Self-Organizing Tree Algorithm; Chapter 6. Data Reduction Using Hierarchical Clustering and Rocchio Bundling; Chapter 7. Intrusion Detection Results; Chapter 8. Web Data Management and Mining; Chapter 9. Effective Web Page Prediction Using Hybrid Model; Chapter 10. Multiple Evidence Combination for WWW Prediction 327 $aChapter 11. WWW Prediction ResultsChapter 12. Multimedia Data Management and Mining; Chapter 13. Image Classification Models; Chapter 14. Subspace Clustering and Automatic Image Annotation; Chapter 15. Enhanced Weighted Feature Selection; Chapter 16. Image Classification and Performance Analysis; Chapter 17. Summary and Directions; APPENDIX A; Data Management Systems: Developments and Trends; Index; Back cover 330 $aFocusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors' own research work, the book takes a practical approach to the subject.The first part of the book reviews data mining techniques, such as artificial neural networks and support vector machines, as well as data mining applications. The second section covers the design and implementation of data mining tools for intrusion detection. It examines v 606 $aData mining 615 0$aData mining. 676 $a005.74 701 $aAwad$b M$g(Mamoun)$01707715 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910809843503321 996 $aDesign and implementation of data mining tools$94096166 997 $aUNINA