in today’s quality- based competitive world, known as knowledge age, customer attraction is of ultimate importance. in respect to the slogan “customer is always right”, customer relation management is the core of an organizational strategy playing an important role in four aspects of customer identification, customer attraction, customer retaining, and customer satisfaction. commercial organiza...

purpose: this study wants to find any relationship between the numbers of purchase and the income the customer brings to the company. the attempt is to find those customers who buy more than one life insurance policy and represent the signs of good payments at the same time by the help of data mining tools. design/ methodology/ approach: the approach of this research is to use data mining tools...

In a practical project a statistical analysis of the Web log files of the domain www.volkswagen.de was carried out by using the CRISP-DM procedure. For the preprocessing phase, more profound findings could be gained than are usually described in many studies. Since the aim was to deduce significant statements while measuring the effect, tests of significance for e-metrics were used in addition ...

In the last years there has been a huge growth and consolidation of the Data Mining field. Some efforts are being done that seek the establishment of standards in the area. Included on these efforts there can be enumerated SEMMA and CRISP-DM. Both grow as industrial standards and define a set of sequential steps that pretends to guide the implementation of data mining applications. The question...

Der Prozess valide, neuartige, potenziell nutzbare und verständliche Muster in Daten zu finden, wird als Knowledge Discovery in Database Prozess bezeichnet (KDD-Prozess). Die diesem Prozess zu Grunde liegende Datenbasis unterliegt einem ständigen Wandel. Doug Laney erkannte die Eigenschaften Volume, Variety und Velocity als neue Herausforderungen für ITOrganisationen. Heute werden diese Herausf...

In this paper, we introduce an integration study which combines Data Mining (DM) and Agent Based Modeling and Simulation (ABMS). This study, as a new paradigm for DM/ABMS, is concerned with two approaches: (i) applying DM techniques in ABMS investigation, and inversely (ii) utilizing ABMS results in DM research. Detailed description of each approach is presented in this paper. A conclusion and ...

This tutorial provides an overview of the data mining process. The tutorial also provides a basic understanding of how to plan, evaluate and successfully refine a data mining project, particularly in terms of model building and model evaluation. Methodological considerations are discussed and illustrated. After explaining the nature of data mining and its importance in business, the tutorial de...

Data mining (DM) technology provides a potential solution to structural health monitoring (SHM) as a deeper data analysis method. In this paper, a comprehensive introduction to the background, definition, function, process, methods and advantage of DM technology is made. The research and application state of DM technology in various fields is reviewed. Responding to the need of SHM and the char...

Terabytes of data are generated everyday in many organizations . To extract hidden predictive information from large volumes of data, data mining (DM) techniques are needed. Organizations are starting to realize the importance of data mining in their strategic planning and successfu l application of DM techniques can be an enormous payoff for the organizations. This paper discusses the requirem...