نتایج جستجو برای: data mining dm
تعداد نتایج: 2463784 فیلتر نتایج به سال:
the rapid growing of information technology (it) motivates and makes competitive advantages in health care industry. nowadays, many hospitals try to build a successful customer relationship management (crm) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. many hospitals have large data warehouses containing customer ...
integrating ahp and data mining for effective retailer segmentation based on retailer lifetime value
data mining techniques have been used widely in the area of customer relationship management (crm). in this study, we have applied data mining techniques to address a problem in business-to-business (b2b) setting. in a manufacturer-retailer-consumer chain, a manufacturer should improve its relationship with retailers to continue its business. segmentation is a useful tool for identifying groups...
Most of graph pattern mining algorithms focus on finding frequent subgraphs and its compact representations, such as closed frequent subgraphs and maximal frequent subgraphs. However, little attention has been paid to mining graph patterns with user-specified significance measure. In this paper, we study a new problem of mining top-k graph patterns that jointly maximize some significance measur...
With the increasing amount of information in electronic form the fields of Machine Learning and Data Mining continue to grow by providing new advances in theory, applications and systems. The aim of this paper is to consider some recent theoretical aspects and approaches to ML and DM with an emphasis on the Italian research.
This paper investigates scalable implementations of out-ofcore I/O-intensive Data Mining algorithms on a ordable parallel architectures, such as clusters of workstations. In order to validate our approach, the K-means algorithm, a well known DM Clustering algorithm, was used as a test case.
Both the number and complexity of Data Mining projects has increased in late years. Unfortunately, nowadays there isn’t a formal process model for this kind of projects, or existing approaches are not right or complete enough. In some sense, present situation is comparable to that in software that led to ’software crisis’ in latest 60’s. Software Engineering matured based on process models and ...
The joint venture of artificial neural network and data mining make the process more perfect, powerful, fast, distributed, fault and noise tolerance and independence of prior assumption. This paper is an overview of artificial neural network, data mining, knowledge management and the purpose of ANN in the field of data mining. Due to the huge amount of data in the data warehouse and data bases,...
Introduction: In recent years, technology advancement and the growth of information technology in organizations have provided a huge source of data stored in the field of drug-related offenses. Analyzing these data and discovering hidden patterns in it can help detect and prevent the occurrence of crimes in this area. This paper aimed to identify the susceptible people to drug trafficking in Si...
Introduction: In recent years, technology advancement and the growth of information technology in organizations have provided a huge source of data stored in the field of drug-related offenses. Analyzing these data and discovering hidden patterns in it can help detect and prevent the occurrence of crimes in this area. This paper aimed to identify the susceptible people to drug trafficking in Si...
Can a model constructed using data mining (DM) programs be trusted? It is known that a decision-tree model can contain relations that are statistically significant, but, in reality, meaningless to a human. When the task is domain analysis, meaningless relations are problematic, since they can lead to wrong conclusions and can consequently undermine a human’s trust in DM programs. To eliminate p...
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