期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2015
卷号：9
期号：1
页码：105-112
DOI：10.14257/ijseia.2015.9.1.09
出版社：SERSC
摘要：In an environment in which several events are sensed in a complex manner and sequentially obtained, a clue can be obtained for inference of situations by classifying each event and analyzing the aspect of change of each event. The study proposes a method to efficiently decide the cluster centers in each subsequent time slot for efficient classification of events and inference of situations in a data stream environment. For the data stream under this condition, each time slot classified at a certain interval is set up, the events using clustering in each time slot are carried out, and to recognize how the aspect of change of each event sensed in a continuous time slot is carried out, the cluster centers are allowed to be rapidly captured.
关键词：Context inference; Data stream; Clustering; k-means; Time slot
