Scalable Multi-Relational Association Mining

Amanda Clare, Hugh E. Williams, Nicholas Lester

Research output: Contribution to conferencePaper

7 Citations (SciVal)

Abstract

We propose the new RADAR technique for multi-relational data mining. This permits the mining of very large collections and provides a new technique for discovering multi-relational associations. Results show that RADAR is reliable and scalable for mining a large yeast homology collection, and that it does not have the main-memory scalability constraints of the Farmer and Warmr tools.
Original languageEnglish
Publication statusPublished - 2004

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