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

Yakub Sebastian, Brian C.S. Loh, Patrick H.H. Then

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

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.

Original languageEnglish
Title of host publicationICDM Workshops 2009 - IEEE International Conference on Data Mining
Pages51-57
Number of pages7
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event2009 IEEE International Conference on Data Mining Workshops, ICDMW 2009 - Miami, FL, United States
Duration: 6 Dec 20096 Dec 2009

Publication series

NameICDM Workshops 2009 - IEEE International Conference on Data Mining

Conference

Conference2009 IEEE International Conference on Data Mining Workshops, ICDMW 2009
CountryUnited States
CityMiami, FL
Period6/12/096/12/09

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