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Knowledge Discovery in Inductive Databases [electronic resource] : Third International Workshop, KDID 2004, Pisa, Italy, September 20, 2004, Revised Selected and Invited Papers / edited by Arno Siebes.

Contributor(s): Siebes, Arno [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Information Systems and Applications, incl. Internet/Web, and HCI: 3377Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005Edition: 1st ed. 2005.Description: VIII, 200 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540318415.Subject(s): Database management | Artificial intelligence | Database Management | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 005.74 Online resources: Click here to access online
Contents:
Invited Paper -- Models and Indices for Integrating Unstructured Data with a Relational Database -- Contributed Papers -- Constraint Relaxations for Discovering Unknown Sequential Patterns -- Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Data -- Theoretical Bounds on the Size of Condensed Representations -- Mining Interesting XML-Enabled Association Rules with Templates -- Database Transposition for Constrained (Closed) Pattern Mining -- An Efficient Algorithm for Mining String Databases Under Constraints -- An Automata Approach to Pattern Collections -- Implicit Enumeration of Patterns -- Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures.
In: Springer Nature eBook
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Invited Paper -- Models and Indices for Integrating Unstructured Data with a Relational Database -- Contributed Papers -- Constraint Relaxations for Discovering Unknown Sequential Patterns -- Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Data -- Theoretical Bounds on the Size of Condensed Representations -- Mining Interesting XML-Enabled Association Rules with Templates -- Database Transposition for Constrained (Closed) Pattern Mining -- An Efficient Algorithm for Mining String Databases Under Constraints -- An Automata Approach to Pattern Collections -- Implicit Enumeration of Patterns -- Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures.

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