Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/84019

Title

A paradigm shift: combined literature and ontology-driven data mining for discovering novel relations in biomedical domain

Author(s)

Sebastian, Y.;  Loh, Brian C. S.;  Then, Patrick H. H.

Abstract

We introduce a novel domain-driven rule discovery and evaluation algorithm based on Swanson's logical relation approach. Over more than a decade, rules have been mined from large biomedical datasets and been evaluated solely based on statistical properties of the rules or user-belief specifications. This approach faces tremendous challenges to determine novel, actionable and interesting rules. In this paper, we introduce a new paradigm in addressing rule interestingness problem using domain knowledge. We demonstrate that novel and interesting association rules can be discovered from large medical datasets based on its ability to infer previously unknown relations in biomedical domain. Our data mining algorithm shows that we can effectively achieve this task by incorporating biomedical domain knowledge by combining both literatures and ontology. We outline the conceptual-architectural framework for future implementation of this methodology.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Sarawak Campus. School of Computing and Design

Source

Proceedings of the 2009 IEEE International Conference on Data Mining (ICDMW 2009), Miami, Florida, United States, 06 December 2009, pp. 51-57

Publication year

2009

Keyword(s)

Algorithms;  Data mining;  Domain knowledge;  Rule evaluation processes;  Swanson's logical relation

Publisher

IEEE

ISBN

9780769539027, 0769539025

Publisher URL

http://dx.doi.org/10.1109/ICDMW.2009.56

Copyright

Copyright © 2009 IEEE.

Peer reviewed