CAJ | 학술논문

SSAS聚类分析是Microsoft SQL Server Analysis Services（SSAS）数据挖掘平台提供的一种重要的数据分析方法,该方法使用迭代技术将数据集中的事例分组为包含类似特征的分类。在聚类方面,SSAS提供了K-means算法和Expectation Maximization算法,其中这两种算法又分为可缩放和不可缩放两种类型。SSAS聚类分析方法在图书馆的读者行为分析中具有较强的可操作性和实用性。
SSAS취류분석시Microsoft SQL Server Analysis Services（SSAS）수거알굴평태제공적일충중요적수거분석방법,해방법사용질대기술장수거집중적사례분조위포함유사특정적분류。재취류방면,SSAS제공료K-means산법화Expectation Maximization산법,기중저량충산법우분위가축방화불가축방량충류형。SSAS취류분석방법재도서관적독자행위분석중구유교강적가조작성화실용성。
SSAS cluster analysis is an important data analysis method provided by the Microsoft SQL Server Analysis Ser- vices (SSAS) data mining platform. This method uses the iterative technique to the classification of instances of the dataset grouped with similar characteristics. In the aspect of clustering, SSAS provides K-means Algorithm and Expectation Maximization Algorithm, which can be further divided into two types:scalable and non-scaling. SSAS cluster analysis has strong maneuverability and practica- bility in the behavioral analysis of library readers.