Given the abundance of event data, the challenge of process mining today is to enable process mining in the large. This research aims to address scalability problem in terms of memory use and time consumption. To this end, we use relational databases as the framework to both store event data and do process mining analysis. We conduct a pre-computation of intermediate structures during insertion...

    This review was conducted between December 2018 and March 2019 at Isfahan University of Medical Sciences. A review of various studies revealed what data mining techniques to predict the probability of survival, what risk factors for these predictions, what criteria for evaluating data mining techniques, and finally what data sources for it have been used to predict the surv...

abandoned surface mine excavations can be a major environmental, social and/or human healthproblem for the mining industry as well as for the community living nearby. this problem is exacerbated by therapidly growing population encroaching on areas of historic mined lands. the aim of this studywas to assess thesafety status of the historic nyala mine excavation with the purpose of coming up wit...

Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database field, the view of data mining as advanced querying has recently stimulated much research into the development of data mining query languages. In the field of machine learning, inductive logic programming has broadened its ...

There is an increase in the demand for data mining applications on the web. With the increase in the size of data sets there is also a demand for scalable generic solutions. Scalability and generic data mining models can be provided with the use of distributed computing. In this paper we propose the use of a multilayered framework for a distributed data mining system. A multi-layered architectu...

classifying customers using data mining algorithms, enables banks to keep old customers loyality while attracting new ones. using decision tree as a data mining technique, we can optimize customer classification provided that the appropriate decision tree is selected. in this article we have presented an appropriate model to classify customers who use internet banking service. the model is deve...