期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2013
卷号：4
期号：4
页码：376-380
语种：English
出版社：Ayushmaan Technologies
摘要：The trajectory of any dynamic object is associated with space and time. The idea of motion would turn meaningless if time is separated from space or vice versa. A novel cascade of space and time was made and named as patiotemporal (ST) in the domain of data mining. Partially ordered sets from a given Boolean ST set are considered to mine patterns. A Cascade Participation Index (CPI) is computed through bottleneck analysis over the data set to measure user interest. Based on this value and the directed graph representation the filtering of irrelevant Cascade Spatiotemporal Patterns (CSTP) can be done having the miner nested in the process. The result has to be extended to real time data sets to prove validation of content.
关键词：Visual Data Mining;explicit data structure;Boolean data;Monotone Boolean Function;Hansel Chains;Binary Hypercube
