Data mining is the process of building predictive or descriptive models based on a large data set, often stored in a relational database. Propositional data mining systems require that the data is converted into one single table. Relational data mining systems, on the other hand, can build models directly from the relational database. While building a model, relational data mining systems execu...

One of the most important issues in all stages of mining study is capital cost estimation. Determination of capital expenditure is a challenging issue for mine designers. In recent decade, quite a few number of studies have focused on proposing estimation models to predict mining capital cost. However, these efforts have not achieved to a predictor model with reliable range of error. Both of ov...

This paper introduces a distributed data mining approach suited to grid computing environments based on a supervised learning classifier system. Different methods of merging data mining models generated at different distributed sites are explored. Centralized Data Mining (CDM) is a conventional method of data mining in distributed data. In CDM, data that is stored in distributed locations have ...

Background and Objective: Colorectal cancer (CRC) is one of the most prevalent malignancies in the world. The early detection of CRC is not only a simple process, but it is also the key to its treatment. Given that data mining algorithms could be potentially useful in cancer prognosis, diagnosis, and treatment, the main focus of this study is to measure the performance of some data mining class...

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...

Data Mining (DM) is a very crucial issue in knowledge discovery processes. The basic facilities to create data mining models were implemented successfully on Oracle 9i as the extension of the database server. DM tools enable developers to create Business Intelligence (BI) applications. As a result Data Mining models can be used as support of knowledge-based management. The main goal of the pape...

The characteristics of virtual organizations present significant challenges to both distributed data mining methods within a metalearning framework and statistical multi-level models. Using hierarchical models, this paper explicitly address the context heterogeneity existing across the partners of virtual organizations. Two new approaches of context-based distributed data mining are analyzed an...

periodic vehicle routing problem focuses on establishing a plan of visits to clients over a given time horizon so as to satisfy some service level while optimizing the routes used in each time period. this paper presents a new effective heuristic algorithm based on data mining tools for periodic vehicle routing problem (pvrp). the related results of proposed algorithm are compared with the resu...