Multi Relational Data Mining
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Multi-Relational Data Mining
With the increased possibilities in modern society for companies and institutions to gather data cheaply and efficiently, the subject of Data Mining has become of increasing importance. This interest has inspired a rapidly maturing research field with developments both on a theoretical, as well as on a practical level with the availability of a range of commercial tools. Unfortunately, the widespread application of this technology has been limited by an important assumption in mainstream Data Mining approaches. This assumption – all data resides, or can be made to reside, in a single table – prevents the use of these Data Mining tools in certain important domains, or requires considerable massaging and altering of the data as a pre-processing step. This limitation has spawned a relatively recent interest in richer Data Mining paradigms that do allow structured data as opposed to the traditional flat representation. This publication goes into the different uses of Data Mining, with Multi-Relational Data Mining (MRDM), the approach to Structured Data Mining, as the main subject of this book.
Relational Data Mining
Author: Saso Dzeroski
language: en
Publisher: Springer Science & Business Media
Release Date: 2001-08
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.
Multi-relational Data Mining
With the increased possibilities in modern society for companies and institutions to gather data cheaply and efficiently, the subject of Data Mining has become of increasing importance. This interest has inspired a rapidly maturing research field with developments both on a theoretical, as well as on a practical level with the availability of a range of commercial tools. Unfortunately, the widespread application of this technology has been limited by an important assumption in mainstream Data Mining approches. This assumption - all data resides, or can be made to reside, in a single table - prevents the use of these Data Mining tools in certain important domains, or requires considerable massaging and altering of the data as a pre-processing step. This liitation has spawned a relatively recent interest in richer Data Mining paradigms that do allow structured data as opposed to the traditional flat representation. This publication goes into the different uses of Data Mining, with Multi-Relational Data Minig (MRDM), the approach to Structured Data Mining, as the main subject of this book.