drug addiction is a major social, economic, and hygienic challenge that impacts on all the community and needs serious threat. available treatments are successful only in short-term unless underlying reasons making individuals prone to the phenomenon are not investigated. nowadays, there are some treatment centers which have comprehensive information about addicted people. therefore, given the ...

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...

Nowadays companies measure suppliers on the basis of a variety of factors and criteria that affect the supplier's selection issue. This paper intended to identify the key effective criteria for selection of green suppliers through an efficient algorithm callediterative process mining or i-PM. Green data were collected first by reviewing the previous studies to identify various environmental cri...

The Transactions in web data often consist of quantitative data, suggesting that fuzzy set theory can be used to represent such data. The time spent by users on each web page is one type of web data, was regarded as a trapezoidal membership function (TMF) and can be used to evaluate user browsing behavior. The quality of mining fuzzy association rules depends on membership functions and since t...

Data Mining is used to discover the knowledge from large amount of databases and transform it into a flexible structure. Association rule mining (ARM) is the essential part of data mining process. Finding good quality of association rules between items in large databases has been an important and challenging association rule mining problem. The rules mined through ARM algorithms are used for de...

In data mining, term frequent pattern extraction is largely used for finding out association rules. Generally association rule mining approaches are used as bottom-up or top-down approach on compressed data structure. In the past, different works proposed different approaches to mine frequent patterns from giving databases. In this paper, we propose a new approach by applying the closed & inter...

We present a simple Data Mining Logic (DML) that can express common data mining tasks, like “Find Boolean association rules” or “Find inclusion dependencies.” At the center of the paper is the problem of characterizing DML queries that are amenable to the levelwise search strategy used in the a-priori algorithm. We relate the problem to that of characterizing monotone first-order properties for...

The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. Due to its high rate of uncertainty and volatility, it carries a higher risk than any other investment area, thus the stock price behavior is difficult to simulation. This paper presents a “data mining-based evolutionary fuzzy expert system” (DEFE...