TY - GEN
T1 - A paradigm shift
T2 - 2009 IEEE International Conference on Data Mining Workshops, ICDMW 2009
AU - Sebastian, Yakub
AU - Loh, Brian C.S.
AU - Then, Patrick H.H.
PY - 2009/12/1
Y1 - 2009/12/1
N2 - 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.
AB - 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.
KW - Biomedical knowledge discovery
KW - Combined literature ontology-based data mining
KW - Domain-driven data mining
KW - Rule interestingness
KW - Swanson's logical relation
UR - http://www.scopus.com/inward/record.url?scp=77951200326&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2009.56
DO - 10.1109/ICDMW.2009.56
M3 - Conference Paper published in Proceedings
AN - SCOPUS:77951200326
SN - 9780769539027
T3 - ICDM Workshops 2009 - IEEE International Conference on Data Mining
SP - 51
EP - 57
BT - ICDM Workshops 2009 - IEEE International Conference on Data Mining
Y2 - 6 December 2009 through 6 December 2009
ER -