business all around the world uses different approaches to know their customers, segment them and formulate suitable strategies for them. one of these approaches is calculating the value of each customer for the company. in this paper by calculating customer lifetime value (clv) for individual customers of an online toy store named alakdolak, three customer segments are extracted. the level of ...

Many interesting real-life mining applications rely on modeling data as sequences of discrete multi-attribute records. Existing literature on sequence mining is partitioned on application-specific boundaries. In this article we distill the basic operations and techniques that are common to these applications. These include conventional mining operations like classification and clustering and se...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers need...

decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. the resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. the most comprehensible decision trees have been designed for perfect symbolic data. classical crisp decision trees (dt) are widely applied to classification t...

decision support systems (dsss) are prevalent information systems for decision making in many competitive business environments. in a dss, decision making process is intimately related to some factors which determine the quality of information systems and their related products. traditional approaches to data analysis usually cannot be implemented in sophisticated companies, where managers nee...

In this participation are discussed principles of bioinformatics, datamining, evolutionary computing and its mutual intersection. Datamining by means of selected evolutionary techniques are discussed with attention on protein structure, segmentation and state of art on the field of evolutionary algorithms use. Basic principles and terminology of evolutionary algorithms, as well as two evolution...

This paper proposes an analytical framework that combines dimension reduction and data mining techniques to obtain a sample segmentation according potential fraud probability. In this regard, the purpose of study is twofold. Firstly, it attempts determine tax benefits are more likely be used by taxpayers means investigating Personal Income Tax structure. Secondly, aims at characterizing through...

In this paper, we describe a segmentation technique that integrates traditional image processing algorithms with techniques adapted from knowledge discovery in databases (KDD) and data mining to analyze and segment unstructured satellite images of natural scenes. We have divided our segmentation task into three major steps. First, an initial segmentation is achieved using dynamic local threshol...

A novel approach utilized in video database objectbased queries is proposed. This new method segments an example video sequence into real world objects using a combination of color image segmentation techniques along with MPEG-1/2 motion vectors. First, the initial frame in the sequence undergoes a color/texture segmentation algorithm that divides the frame into homogenous regions of color and ...