TY - GEN
T1 - Bidirectional mining of non-redundant recurrent rules from a sequence database
AU - Lo, David
AU - Ding, Bolin
AU - Lucia,
AU - Han, Jiawei
PY - 2011
Y1 - 2011
N2 - We are interested in scalable mining of a non-redundant set of significant recurrent rules from a sequence database. Recurrent rules have the form whenever a series of precedent events occurs, eventually a series of consequent events occurs. They are intuitive and characterize behaviors in many domains. An example is the domain of software specification, in which the rules capture a family of properties beneficial to program verification and bug detection. We enhance a past work on mining recurrent rules by Lo, Khoo, and Liu to perform mining more scalably. We propose a new set of pruning properties embedded in a new mining algorithm. Performance and case studies on benchmark synthetic and real datasets show that our approach is much more efficient and outperforms the state-of-the-art approach in mining recurrent rules by up to two orders of magnitude.
AB - We are interested in scalable mining of a non-redundant set of significant recurrent rules from a sequence database. Recurrent rules have the form whenever a series of precedent events occurs, eventually a series of consequent events occurs. They are intuitive and characterize behaviors in many domains. An example is the domain of software specification, in which the rules capture a family of properties beneficial to program verification and bug detection. We enhance a past work on mining recurrent rules by Lo, Khoo, and Liu to perform mining more scalably. We propose a new set of pruning properties embedded in a new mining algorithm. Performance and case studies on benchmark synthetic and real datasets show that our approach is much more efficient and outperforms the state-of-the-art approach in mining recurrent rules by up to two orders of magnitude.
UR - http://www.scopus.com/inward/record.url?scp=79957854311&partnerID=8YFLogxK
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U2 - 10.1109/ICDE.2011.5767848
DO - 10.1109/ICDE.2011.5767848
M3 - Conference contribution
AN - SCOPUS:79957854311
SN - 9781424489589
T3 - Proceedings - International Conference on Data Engineering
SP - 1043
EP - 1054
BT - 2011 IEEE 27th International Conference on Data Engineering, ICDE 2011
T2 - 2011 IEEE 27th International Conference on Data Engineering, ICDE 2011
Y2 - 11 April 2011 through 16 April 2011
ER -