Behaviour scoring is used in several companies to score the customers according to credit risk by analyzing historical data about their past behaviour. In this paper we describe a data mining approach to credit risk evaluation in a Portuguese telecommunication company.

This paper describes a mineral exploration project conducted by a junior mining company within a probabilistic framework. In particular, it shows how beliefs about a project can be updated in response to a series of new pieces of information about the project associated with exploration activities using subjective probabilities. Several alternative frameworks are briefly mentioned as ways to im...

To overcome the product overload of Internet shoppers, we introduce a semantic recommendation procedure which is more efficient when applied to Internet shopping malls. The suggested procedure recommends the semantic products to the customers and is originally based on Web usage mining, product classification, association rule mining, and frequently purchasing. We applied the procedure to the d...

Reading manually annual and quarterly reports helps financial analysts and decision makers to judge companies’ financial performance. Professionals infer from a report not only the current financial performance and strategic outlook of a company but also its prospective financial performance. They have insightful methods to find some intuitive indications of the future financial performance of ...

Information system and data mining are important resources for the investors to make decisions. Information theory pointed that the information is increasing all the time, when the corporations build their millions of databases in order to improve the efficiency. Database technology caters to the needs of fully developing the information resources. This essay discusses the problem of decision m...

This paper describes experiments in applying data mining techniques to historical data collected by network monitoring agents. Large amounts of performance data, including network, system, and application performance data, are collected and stored by monitoring agents. Data mining algorithms analyze the data and codify it into usable knowledge. We show, via experiments, that the knowledge conta...

The ITIL framework is the best known set of best practices for managing IT services. In this paper we introduce process mining as a useful technique for assessing whether a business process is implemented according to ITIL guidelines. We evaluated our approach using a real-world case study in an IT vendor developing a complex software platform. The company receives thousands of requests (includ...

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 ...

In this emerging trend, it is necessary to understand the recent developments taking place in the field of opinion mining and sentiment analysis (OMSA) as part of text mining in social networks, which plays an important role for decision making process to the organization or company, Government and general public. In this paper, we present the recent role of OMSA in Social Networks with differe...

Data Mining tools and methods can be used to facilitate auditors to issue their opinions. Numerous of these methods have not yet been tested for the purpose of discriminating cases of qualified opinions. In this study we employ three Data Mining classification techniques to develop models capable to predict qualified auditors’ reports. The input vector is composed of quantitative and qualitativ...