PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Scalability and efficiency in multi-relational data mining
Hendrik Blockeel and Michele Sebag
ACM SIGKDD, Special Issue on Multi-Relational Data Mining Volume 5, Number 1, pp. 17-30, 2003.

Abstract

Efficiency and scalability have always been important concerns in the field of data mining, and are even more so in the multi-relational context, which is inherently more complex. The issue has been receiving an increasing amount of attention during the last few years, and quite a number of theoretical results, algorithms and implementations have been presented that explicitly aim at improving the eciency and scalability of multi-relational data mining approaches. With this article we attempt to present a structured overview.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:517
Deposited By:Michele Sebag
Deposited On:24 December 2004