期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2015
卷号：5
期号：1
页码：51
DOI：10.5121/ijdkp.2015.5105
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Big data quickly comes under the spotlight in recent years. As big data is supposed to handle extremelyhuge amount of data, it is quite natural that the demand for the computational environment to accelerates,and scales out big data applications increases. The important thing is, however, the behavior of big dataapplications is not clearly defined yet. Among big data applications, this paper specifically focuses onstream mining applications. The behavior of stream mining applications varies according to thecharacteristics of the input data. The parameters for data characterization are, however, not clearlydefined yet, and there is no study investigating explicit relationships between the input data, and streammining applications, either. Therefore, this paper picks up frequent pattern mining as one of therepresentative stream mining applications, and interprets the relationships between the characteristics ofthe input data, and behaviors of signature algorithms for frequent pattern mining.
