TY - GEN
T1 - Hybrid technique for frequent pattern extraction from Sequential Database
AU - Selvaraj, Rajalakshmi
AU - Kuthadi, Venu Madhav
AU - Marwala, Tshilidzi
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2014
Y1 - 2014
N2 - Data mining has became a familiar tool for mining stored value from the large scale databases that are known as Sequential Database. These databases has large number of itemsets that can arrive frequently and sequentially, it can also predict the users behaviors. The evaluation of user behavior is done by using Sequential pattern mining where the frequent patterns extracted with several limitations. Even the previous sequential pattern techniques used some limitations to extract those frequent patterns but these techniques does not generated the more reliable patterns .Thus, it is very complex to the decision makers for evaluation of user behavior. In this paper, to solve this problem a technique called hybrid pattern is used which has both time based limitation and space limitation and it is used to extract more feasible pattern from sequential database. Initially, the space limitation is applied to break the sequential database using the maximum and minimum threshold values. To this end, the time based limitation is applied to extract more feasible patterns where a bury-time arrival rate is computed to extract the reliable patterns.
AB - Data mining has became a familiar tool for mining stored value from the large scale databases that are known as Sequential Database. These databases has large number of itemsets that can arrive frequently and sequentially, it can also predict the users behaviors. The evaluation of user behavior is done by using Sequential pattern mining where the frequent patterns extracted with several limitations. Even the previous sequential pattern techniques used some limitations to extract those frequent patterns but these techniques does not generated the more reliable patterns .Thus, it is very complex to the decision makers for evaluation of user behavior. In this paper, to solve this problem a technique called hybrid pattern is used which has both time based limitation and space limitation and it is used to extract more feasible pattern from sequential database. Initially, the space limitation is applied to break the sequential database using the maximum and minimum threshold values. To this end, the time based limitation is applied to extract more feasible patterns where a bury-time arrival rate is computed to extract the reliable patterns.
KW - Data mining
KW - Hybrid pattern mining
KW - Sequential pattern
UR - http://www.scopus.com/inward/record.url?scp=84910639399&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11933-5_29
DO - 10.1007/978-3-319-11933-5_29
M3 - Conference contribution
AN - SCOPUS:84910639399
T3 - Advances in Intelligent Systems and Computing
SP - 265
EP - 275
BT - Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing
A2 - Udgata, Siba K.
A2 - Biswal, Bhabendra Narayan
A2 - Mandal, Jyotsna Kumar
A2 - Satapathy, Suresh Chandra
PB - Springer Verlag
T2 - 3rd International Conference on Frontiers in Intelligent Computing: Theory and Applications, FICTA-2014
Y2 - 14 November 2014 through 15 November 2014
ER -