Inductive Databases and Constraint-Based Data Mining
This book presents inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The book provides an overview of the state-of-the art in this novel research area. Of special interest are the recent methods for constrai...
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| Other Authors: | , , |
| Format: | Electronic |
| Language: | English |
| Published: |
New York, NY :
Springer New York,
2010.
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| Subjects: | |
| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4419-7738-0 |
Table of Contents:
- Part 1 Introduction & Framework
- Twelve Years After: A Historical Perspective on Inductive Databases
- A Data Mining Framework and Ontology
- Data Mining Query Languages, Mining Views, and Algebras
- The Assessment of Data Mining Results through Randomization
- Part 2 Constraint-based Mining Techniques
- Generalizing Item set Mining in a Constraint Programming Setting From Local Patterns to Classification Models
- Constrained Induction of Predictive Clustering Trees
- Constrained Clustering: An Overview
- Probabilistic Inductive Querying Using ProbLog
- Part 3 Inductive Databases: Integration Approaches
- An Inductive Database based on Mining
- SINDBAD and SiQL: An Inductive Database and Query Language in the Relational Model Experiment Databases
- Inductive Scientific Databases for Equation Discovery
- Part 4 Applications in Bioinformatics
- Robot Scientists, Inductive Queries, and Drug Design
- Predicting Gene Function using Predictive Clustering Trees
- Analysis of Gene Expression Data with Predictive Clustering Trees Using a Solver Over String Pattern Domain to Analyse Gene Promoter Sequences.