| 000 | 00865camuu22002774a 4500 | |
| 001 | 000000872561 | |
| 005 | 20040305162605 | |
| 008 | 010730s2001 gw a b 001 0 eng | |
| 010 | ▼a ?01049336 | |
| 020 | ▼a 3540422897 (alk. paper) | |
| 040 | ▼a DLC ▼c DLC ▼d OHX ▼d C#P ▼d UKM ▼d 211009 | |
| 042 | ▼a pcc | |
| 049 | 1 | ▼l 111276825 |
| 050 | 0 0 | ▼a QA76.9.D3 ▼b R452 2001 |
| 082 | 0 0 | ▼a 006.3 ▼2 21 |
| 090 | ▼a 006.3 ▼b R382 | |
| 245 | 0 0 | ▼a Relational data mining / ▼c Saso Dzeroski, Nada Lavrac (eds.). |
| 260 | ▼a Berlin ; ▼a New York : ▼b Springer, ▼c c2001. | |
| 300 | ▼a xix, 398 p. : ▼b ill. ; ▼c 24 cm. | |
| 504 | ▼a Includes bibliographical references and indexes. | |
| 650 | 0 | ▼a Database management. |
| 650 | 0 | ▼a Relational databases. |
| 650 | 0 | ▼a Data mining. |
| 700 | 1 | ▼a Dzeroski, Saso , ▼d 1968- |
| 700 | 1 | ▼a Lavrac, Nada. |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 중앙도서관/서고6층/ | 청구기호 006.3 R382 | 등록번호 111276825 (2회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining.
This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.
As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining.
This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.
New feature
As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area.The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining.
This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.
정보제공 :
목차
I. Introduction.- 1. Data Mining in a Nutshell.- 2. Knowledge Discovery in Databases: An Overview.- 3. An Introduction to Inductive Logic Programming.- 4. Inductive Logic Programming for Knowledge Discovery in Databases.- II. Techniques.- 5. Three Companions for Data Mining in First Order Logic.- 6. Inducing Classification and Regression Trees in First Order Logic.- 7. Relational Rule Induction with CProgol4.4: A Tutorial Introduction.- 8. Discovery of Relational Association Rules.- 9. Distance Based Approaches to Relational Learning and Clustering.- III. From Propositional to Relational Data Mining.- 10. How to Upgrade Propositional Learners to First Order Logic: A Case Study.- 11. Propositionalization Approaches to Relational Data Mining.- 12. Relational Learning and Boosting.- 13. Learning Probabilistic Relational Models.- IV. Applications and Web Resources.- 14. Relational Data Mining Applications: An Overview.- 15. Four Suggestions and a Rule Concerning the Application of ILP.- 16. Internet Resources on ILP for KDD.- Author Index.
정보제공 :