TY - GEN
T1 - Common sense knowledge based hybrid interestingness measures for data mining
AU - Lee, Ingi
AU - Yong, Hwan Seung
PY - 2012
Y1 - 2012
N2 - The association rule mining is now widely used in many fields such as commerce, telecom, insurance, and bioinformatics. Though it is improved in performance, the real commerce database size and dimension has greatly increased to a point of creating thousands or millions of association rules. In spite of using minimum support and confidence thresholds to help weed out or exclude the exploration of uninteresting rules, many rules that are not interesting to the user may still be produced. We develop intelligent data mining technique that generate and evaluate association rules by hybrid interestingness measures based common sense knowledge. We provide new and interesting knowledge to users by Common-Sense Measures. We define a Common-Sense Measures by similarity between association rules and common sense knowledge. This measure is based on the common sense knowledge network.
AB - The association rule mining is now widely used in many fields such as commerce, telecom, insurance, and bioinformatics. Though it is improved in performance, the real commerce database size and dimension has greatly increased to a point of creating thousands or millions of association rules. In spite of using minimum support and confidence thresholds to help weed out or exclude the exploration of uninteresting rules, many rules that are not interesting to the user may still be produced. We develop intelligent data mining technique that generate and evaluate association rules by hybrid interestingness measures based common sense knowledge. We provide new and interesting knowledge to users by Common-Sense Measures. We define a Common-Sense Measures by similarity between association rules and common sense knowledge. This measure is based on the common sense knowledge network.
KW - Common Sense Knowledge
KW - Data Mining
KW - Interestingness Measures
KW - Knowledge Representation
KW - Semantic Network
KW - Similarity
UR - http://www.scopus.com/inward/record.url?scp=84866018785&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-32645-5_19
DO - 10.1007/978-3-642-32645-5_19
M3 - Conference contribution
AN - SCOPUS:84866018785
SN - 9783642326448
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 146
EP - 154
BT - Convergence and Hybrid Information Technology - 6th International Conference, ICHIT 2012, Proceedings
T2 - 6th International Conference on Convergence and Hybrid Information Technology, ICHIT 2012
Y2 - 23 August 2012 through 25 August 2012
ER -