Organizations must improve decisional quality, and the continuous usage of data mining techniques is a crucial issue for management. This mostly involves an individual's motivation to engage in behavior. could perhaps be characterized terms working regimen. technology utilization employee activity are two main difficulties that this dilemma revolves around. study aims address aspect associated ...

Spurred by developments such as cloud computing, there has been considerable recent interest in the paradigm of datamining-as-service. A company (data owner) lacking in expertise or computational resources can outsource its mining needs to a third party service provider (server). However, both the items and the association rules of the outsourced database are considered private property of the ...

At Silicon Graphics, Inc., we have developed a data mining and visualization product called MineSet(Silicon Graphics 1998, Brunk, Kelly & Kohavi 1997). MineSet first released in early 1996 mostly as a visualization product and then became a full data mining and visualization product late that year with several data mining algorithms based onMLC++ (Kohavi, Sommerfield & Dougherty 1997). The engi...

Abstract— The increasing facility to track and collect large amounts of data with the use of this has led to an interest in the development of data mining algorithms which preserve user privacy. With the growth of data analysis and processing technique, the privacy disclosure problem about individual or company is inevitably exposed when releasing or sharing data to mine useful decision informa...

Customer Relationship Management (CRM) system is used to manage company relations with the existing and prospect customers. Data mining is used in organization for decision making and forecasting of prospective customers. We have studied recent literature related to use of data mining techniques for CRM. Based on review of the contemporary literature, we analyzed different data mining technique...

New age telecommunication sector (GSM) has been based on new customer acquisition plans and tactics. For this purpose, evaluation of the call traffic data from the data warehouses and making some predictions by data mining algorithms are so important. Data mining is a process for filtering massive amounts of data to find useful information to optimize decision making in the firms. Data mining m...

Preserve knowledge, retain know, these are the objectives of a scalable company. The knowledge mapping is graphical techniques which allows preserve and visualize the strategic heritage of the acquired know-how during the years. We use Data mining techniques to exploit the different sources of data and to improve the process of acquiring this knowledge. In this paper, we present a new knowledge...

In the information age, the availability of data on consumer profiles has opened new possibilities for companies to increase their revenue via data mining techniques. One approach has been to strategically set prices of various products, taking into account the profiles of consumers. We study algorithms for the multi-product pricing problem, where, given consumer preferences among products, the...

Project management is becoming an important key process in industrial engineering in order to choose suitable and profitable projects for the companies. We have focused our interest from the manager point of view that needs quality data to make decisions about which kind of projects are more suitable for the company. But nowadays the suitability of the projects don’t depend only on quantitative...

Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools provide a useful for alternative framework that addresses this problem. This study follows a DM technique to identify diabetic patients. We develop a model that clusters diabetes patients of a large healthcare company into different subpopulation. Consequently, we show the value of applying a DM ...