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Database support for data mining applications : discovering knowledge with inductive queries

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Database support for data mining applications : discovering knowledge with inductive queries
Original Title Database support for data mining applications : discovering knowledge with inductive queries
Author Meo, Rosa, Lanzi, Pier Luca, 1967-, Klemettinen, Mika
Publication date

Topics Data mining, Database searching, Database management, Databases
Publisher Berlin , New York : Springer
Collection folkscanomy_miscellaneous, folkscanomy, additional_collections
Language English
Book Type EBook
Material Type Book
File Type PDF
Downloadable Yes
Support Mobile, Desktop, Tablet
Scan Quality: Best No watermark
PDF Quality: Good
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Price 0.00
Submitted By
Sketch the Cow
Submit Date December 29, 2015
Database Support for Data Mining Applications: Discovering Knowledge with Inductive Queries
Author: Rosa Meo, Pier Luca Lanzi, Mika Klemettinen
Published by Springer Berlin Heidelberg
ISBN: 978-3-540-22479-2
DOI: 10.1007/b99016

Table of Contents:

  • Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach
  • Query Languages Supporting Descriptive Rule Mining: A Comparative Study
  • Declarative Data Mining Using SQL3
  • Towards a Logic Query Language for Data Mining
  • A Data Mining Query Language for Knowledge Discovery in a Geographical Information System
  • Towards Query Evaluation in Inductive Databases Using Version Spaces
  • The GUHA Method, Data Preprocessing and Mining
  • Constraint Based Mining of First Order Sequences in SeqLog
  • Interactivity, Scalability and Resource Control for Efficient KDD Support in DBMS
  • Frequent Itemset Discovery with SQL Using Universal Quantification
  • Deducing Bounds on the Support of Itemsets
  • Model-Independent Bounding of the Supports of Boolean Formulae in Binary Data
  • Condensed Representations for Sets of Mining Queries
  • One-Sided Instance-Based Boundary Sets
  • Domain Structures in Filtering Irrelevant Frequent Patterns
  • Integrity Constraints over Association Rules

Includes bibliographical references and author index

Database languages and query execution — Support for KDD-process

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