Somek Mario, Hercigonja-Szekeres Mira
University of Applied Health Sciences, Zagreb, Croatia.
Stud Health Technol Inform. 2017;244:53-57.
The amount of stored data in health information systems can reach tera- and petabytes and application of specific algorithms in the field of data mining makes finding useful information suitable for making quality business decisions. A frequently used method for determining the rules of the relationship between attributes is the Association rule by applying Apriori algorithm. Lack of basic Apriori algorithm is derived from the slow work due to multiple scanned data sets. By examining the speed of generating the basic rules in relation to the improved Apriori algorithm by using software RapidMiner confirmed that the time required to generate rules for Improved algorithm is shorter, the rules are quickly generated particularly for large data sets, which is an advantage for making decisions.
健康信息系统中存储的数据量可达太字节和拍字节，数据挖掘领域中特定算法的应用使得找到适合做出高质量商业决策的有用信息成为可能。确定属性之间关系规则的一种常用方法是应用Apriori算法的关联规则。基本Apriori算法的缺点源于对多个数据集进行扫描导致工作速度缓慢。通过使用RapidMiner软件检查生成基本规则与改进的Apriori算法相关的速度，证实了改进算法生成规则所需的时间更短，特别是对于大数据集能够快速生成规则，这对于决策而言是一个优势。
