Knowledge Discovery In Inductive Databases
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Author |
: Saso Dzeroski |
Publisher |
: Springer |
Total Pages |
: 310 |
Release |
: 2007-09-29 |
ISBN-10 |
: 9783540755494 |
ISBN-13 |
: 3540755497 |
Rating |
: 4/5 (94 Downloads) |
Synopsis Knowledge Discovery in Inductive Databases by : Saso Dzeroski
This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006, held in association with ECML/PKDD. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.
Author |
: Bart Goethals |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 197 |
Release |
: 2005-02-23 |
ISBN-10 |
: 9783540250821 |
ISBN-13 |
: 3540250824 |
Rating |
: 4/5 (21 Downloads) |
Synopsis Knowledge Discovery in Inductive Databases by : Bart Goethals
This book constitutes the thoroughly refereed joint postproceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases, KDID 2004, held in Pisa, Italy in September 2004 in association with ECML/PKDD. Inductive Databases support data mining and the knowledge discovery process in a natural way. In addition to usual data, an inductive database also contains inductive generalizations, like patterns and models extracted from the data. This book presents nine revised full papers selected from 23 submissions during two rounds of reviewing and improvement together with one invited paper. Various current topics in knowledge discovery and data mining in the framework of inductive databases are addressed.
Author |
: Francesco Bonchi |
Publisher |
: Springer |
Total Pages |
: 259 |
Release |
: 2006-03-05 |
ISBN-10 |
: 9783540332930 |
ISBN-13 |
: 3540332936 |
Rating |
: 4/5 (30 Downloads) |
Synopsis Knowledge Discovery in Inductive Databases by : Francesco Bonchi
This book presents the thoroughly refereed joint postproceedings of the 4th International Workshop on Knowledge Discovery in Inductive Databases, October 2005. 20 revised full papers presented together with 2 are reproduced here. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.
Author |
: Saso Dzeroski |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 422 |
Release |
: 2001-08 |
ISBN-10 |
: 3540422897 |
ISBN-13 |
: 9783540422891 |
Rating |
: 4/5 (97 Downloads) |
Synopsis Relational Data Mining by : Saso Dzeroski
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.
Author |
: Oded Z. Maimon |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 1436 |
Release |
: 2005 |
ISBN-10 |
: 0387244352 |
ISBN-13 |
: 9780387244358 |
Rating |
: 4/5 (52 Downloads) |
Synopsis Data Mining and Knowledge Discovery Handbook by : Oded Z. Maimon
Organizes major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD). This book provides algorithmic descriptions of classic methods, and also suitable for professionals in fields such as computing applications, information systems management, and more.
Author |
: |
Publisher |
: |
Total Pages |
: 276 |
Release |
: 2005 |
ISBN-10 |
: UOM:39015069189085 |
ISBN-13 |
: |
Rating |
: 4/5 (85 Downloads) |
Synopsis Knowledge Discovery in Inductive Databases by :
Author |
: Jean-Francois Boulicaut |
Publisher |
: Springer |
Total Pages |
: 409 |
Release |
: 2006-02-08 |
ISBN-10 |
: 9783540313519 |
ISBN-13 |
: 3540313516 |
Rating |
: 4/5 (19 Downloads) |
Synopsis Constraint-Based Mining and Inductive Databases by : Jean-Francois Boulicaut
The interconnected ideas of inductive databases and constraint-based mining are appealing and have the potential to radically change the theory and practice of data mining and knowledge discovery. This book reports on the results of the European IST project "cInQ" (consortium on knowledge discovery by Inductive Queries) and its final workshop entitled Constraint-Based Mining and Inductive Databases organized in Hinterzarten, Germany in March 2004.
Author |
: Rosa Meo |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 336 |
Release |
: 2004-07-28 |
ISBN-10 |
: 9783540224792 |
ISBN-13 |
: 3540224793 |
Rating |
: 4/5 (92 Downloads) |
Synopsis Database Support for Data Mining Applications by : Rosa Meo
Data mining from traditional relational databases as well as from non-traditional ones such as semi-structured data, Web data, and scientific databases housing biological, linguistic, and sensor data has recently become a popular way of discovering hidden knowledge. This book on database support for data mining is developed to approaches exploiting the available database technology, declarative data mining, intelligent querying, and associated issues, such as optimization, indexing, query processing, languages, and constraints. Attention is also paid to the solution of data preprocessing problems, such as data cleaning, discretization, and sampling. The 16 reviewed full papers presented were carefully selected from various workshops and conferences to provide complete and competent coverage of the core issues. Some papers were developed within an EC funded project on discovering knowledge with inductive queries.
Author |
: Sašo Džeroski |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 458 |
Release |
: 2010-11-18 |
ISBN-10 |
: 9781441977380 |
ISBN-13 |
: 1441977384 |
Rating |
: 4/5 (80 Downloads) |
Synopsis Inductive Databases and Constraint-Based Data Mining by : Sašo Džeroski
This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The aim of the book as to provide an overview of the state-of- the art in this novel and - citing research area. Of special interest are the recent methods for constraint-based mining of global models for prediction and clustering, the uni?cation of pattern mining approaches through constraint programming, the clari?cation of the re- tionship between mining local patterns and global models, and the proposed in- grative frameworks and approaches for inducive databases. On the application side, applications to practically relevant problems from bioinformatics are presented. Inductive databases (IDBs) represent a database view on data mining and kno- edge discovery. IDBs contain not only data, but also generalizations (patterns and models) valid in the data. In an IDB, ordinary queries can be used to access and - nipulate data, while inductive queries can be used to generate (mine), manipulate, and apply patterns and models. In the IDB framework, patterns and models become ”?rst-class citizens” and KDD becomes an extended querying process in which both the data and the patterns/models that hold in the data are queried.
Author |
: Animesh Adhikari |
Publisher |
: Springer |
Total Pages |
: 0 |
Release |
: 2015-01-19 |
ISBN-10 |
: 3319132113 |
ISBN-13 |
: 9783319132112 |
Rating |
: 4/5 (13 Downloads) |
Synopsis Advances in Knowledge Discovery in Databases by : Animesh Adhikari
This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases. Various interesting and intelligent algorithms are reported on data mining tasks. A large number of association measures are presented, which play significant roles in decision support applications. This book presents, discusses and contrasts new developments in mining time-stamped data, time-based data analyses, the identification of temporal patterns, the mining of multiple related databases, as well as local patterns analysis.