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Knowledge Discovery in Inductive Databases

Overview of attention for book
Cover of 'Knowledge Discovery in Inductive Databases'

Table of Contents

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    Book Overview
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    Chapter 1 Models and Indices for Integrating Unstructured Data with a Relational Database
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    Chapter 2 Constraint Relaxations for Discovering Unknown Sequential Patterns
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    Chapter 3 Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Data
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    Chapter 4 Theoretical Bounds on the Size of Condensed Representations
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    Chapter 5 Knowledge Discovery in Inductive Databases
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    Chapter 6 Database Transposition for Constrained (Closed) Pattern Mining
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    Chapter 7 An Efficient Algorithm for Mining String Databases Under Constraints
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    Chapter 8 An Automata Approach to Pattern Collections
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    Chapter 9 Implicit Enumeration of Patterns
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    Chapter 10 Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures
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Citations

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Chapter title
Knowledge Discovery in Inductive Databases
Chapter number 5
Book title
Knowledge Discovery in Inductive Databases
Published in
Lecture notes in computer science, January 2005
DOI 10.1007/978-3-540-31841-5_5
Book ISBNs
978-3-54-025082-1, 978-3-54-031841-5
Authors

Bart Goethals, Arno Siebes, Ling Feng, Tharam Dillon, Feng, Ling, Dillon, Tharam

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 33%
Researcher 2 33%
Unknown 2 33%
Readers by discipline Count As %
Computer Science 4 67%
Unknown 2 33%

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