Multi-Relational Data Mining Task

From GM-RKB
(Redirected from Multi-Relational Learning)
Jump to navigation Jump to search

A Multi-Relational Data Mining Task is a data mining task whose input is a multi-relational database (that cannot make an iid assumption).



References

2011

2011

2008

2003

  • (Džeroski, 2003) ⇒ Sašo Džeroski. (2003). “Multi-Relational Data Mining: an introduction.” In: ACM SIGKDD Explorations Newsletter, 5(1). doi:10.1145/959242.959245
    • ABSTRACT: Data mining algorithms look for patterns in data. While most existing data mining approaches look for patterns in a single data table, multi-relational data mining (MRDM) approaches look for patterns that involve multiple tables (relations) from a relational database. In recent years, the most common types of patterns and approaches considered in data mining have been extended to the multi-relational case and MRDM now encompasses multi-relational (MR) association rule discovery, MR decision trees and MR distance-based methods, among others. MRDM approaches have been successfully applied to a number of problems in a variety of areas, most notably in the area of bioinformatics. This article provides a brief introduction to MRDM, while the remainder of this special issue treats in detail advanced research topics at the frontiers of MRDM.