TY - GEN
T1 - Mining single pass weighted pattern tree
AU - Castelino, Olivia
AU - Kumar, Preetham
AU - Maddodi, Srivatsa
PY - 2012/3/15
Y1 - 2012/3/15
N2 - Weighted tree mining has become an important research topic in Data mining. There are several algorithms for mining Frequent Pattern trees. FP growth algorithm using FP tree has been considered for frequent pattern mining because of its enormous performance and development compared to the candidate generation model of Apriori. The purpose of our work is to provide a tree structure for incremental and interactive weighted pattern mining by only one database scan. It is applied to existing Compact pattern (CP) tree. CP tree dynamically achieves frequency-descending prefix tree structure with a single-pass by applying tree restructuring technique and considerably reducing the mining time. It is competent of using prior tree structures and acquires mining outcomes to decrease the computation by incredible amount. Performance analysis show that our tree structure is very efficient for incremental and interactive weighted pattern mining.
AB - Weighted tree mining has become an important research topic in Data mining. There are several algorithms for mining Frequent Pattern trees. FP growth algorithm using FP tree has been considered for frequent pattern mining because of its enormous performance and development compared to the candidate generation model of Apriori. The purpose of our work is to provide a tree structure for incremental and interactive weighted pattern mining by only one database scan. It is applied to existing Compact pattern (CP) tree. CP tree dynamically achieves frequency-descending prefix tree structure with a single-pass by applying tree restructuring technique and considerably reducing the mining time. It is competent of using prior tree structures and acquires mining outcomes to decrease the computation by incredible amount. Performance analysis show that our tree structure is very efficient for incremental and interactive weighted pattern mining.
UR - http://www.scopus.com/inward/record.url?scp=84858056624&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84858056624&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-27872-3_18
DO - 10.1007/978-3-642-27872-3_18
M3 - Conference contribution
AN - SCOPUS:84858056624
SN - 9783642278716
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 117
EP - 124
BT - Data Engineering and Management - Second International Conference, ICDEM 2010, Revised Selected Papers
T2 - 2nd International Conference on Data Engineering and Management, ICDEM 2010
Y2 - 29 July 2010 through 31 July 2010
ER -