Data mining from multiple heterogeneous relational databases using decision tree classification
| Autor: | Abdelouahab Moussaoui, Tahar Mehenni |
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| Rok vydání: | 2012 |
| Předmět: |
Computer science
Relational database Decision tree Probabilistic database computer.software_genre Database design Candidate key Artificial Intelligence Signal Processing Semi-structured data Database theory Computer Vision and Pattern Recognition Data mining Change data capture computer Software Database model |
| Zdroj: | Pattern Recognition Letters. 33:1768-1775 |
| ISSN: | 0167-8655 |
| DOI: | 10.1016/j.patrec.2012.05.014 |
| Popis: | Nowadays, the expansion of computer networks and the diversity of data sources require new data mining approaches in multi-database systems. We propose a classification approach across multiple heterogeneous relational databases. More specifically, given a set of inter-related databases, we use a regression model for predicting the most useful links that will be connected to build a multi-relational decision tree. Experiments performed on different real and synthetic databases were very satisfactory compared with previous classification approaches in multiple databases. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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