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 handleextremely huge amount of data, it is quite natural that the demand for the computationalenvironment to accelerates, and scales out big data applications increases. The important thingis, however, the behavior of big data applications is not clearly defined yet. Among big dataapplications, this paper specifically focuses on stream mining applications. The behavior ofstream mining applications varies according to the characteristics of the input data. Theparameters for data characterization are, however, not clearly defined yet, and there is no studyinvestigating explicit relationships between the input data, and stream mining applications,either. Therefore, this paper picks up frequent pattern mining as one of the representativestream mining applications, and interprets the relationships between the characteristics of theinput data, and behaviors of signature algorithms for frequent pattern mining.
