Data mining holds the promise of extracting unsuspected information from very large databases. Methods have been developed to build association rules from large data sets. Association rules indicate the strength of association of two or more data attributes. In many ways, the interest in association rules is that they offer the promise (or illusion) of causal, or at least, predictive relationsh...

The Convention concerning the Prohibition and Immediate Action for the Elimination of the Worst Forms of Child Labour was adopted by the International Labour Organization in 1999. 174 countries around the world have signed or ratified the convention, which requires countries to adopt laws and implement programs to prohibit and eliminate child labor that poses harms to health or safety. Nonethel...

One of the most interesting issues in agent technology has always been the modeling and enhancement of agent behavior. Numerous approaches exist, attempting to optimally reflect both the inner states, as well as the perceived environment of an agent, in order to provide it either with reactivity or proactivity. Within the context of this paper, an alternative methodology for enhancing agent beh...

Data mining and multiagent approach has been used successfully in the development of large complex systems. Agents are used to perform some action or activity on behalf of a user of a computer system. The study proposes an agent based algorithm PrePZero-r using Zero-R algorithm in Weka. Algorithms are powerful technique for solution of various combinatorial or optimization problems. Zero-R is a...

The paper proposes a linguistics-based text mining approach to demonstrate the process of extracting financial concepts from the Security Exchange Commission (SEC) litigation releases (LR). The proposed approach presents the extracted information as a knowledge base to be used in market monitoring surveillance systems. Also, it facilitates users’ acquisition, maintenance and access to financial...

By analyzing historical data sequences and identifying relations between the occurring of data items and certain types of business events we have opportunities to gain insights into future status and thereby take action proactively. This paper proposes a new approach to cope with the problem of prediction on data sequence characterized by multiple dimensions. The proposed relation mining approa...

Draft Background The aim of this paper is to present an outline for discussion upon a new Research Challenge on Opinion Mining and Sentiment Analysis. This research challenge has been developed in the scope of project CROSSOVER “Bridging Communities for Next Generation Policy-Making” in the view of the definition of a new Research Roadmap on ICT Tools for Governance and Policy Making, building ...

This paper proposes a method that discovers time series event patterns from textual data with time information. The patterns are composed of sequences of events and each event is extracted from the textual data, where an event is characteristic content included in the textual data such as a company name, an action, and an impression of a customer. The method introduces 7 types of time constrain...

In current market scenarios, telecom companies are quite competitive and look forward to have lion’s share in the market by winning new and withholding existing customers. Customers who are lost to competitor are known as Churned customers and can be retain by adopting Churn prevention model. For a given dataset, this model predicts the list of customers to be churned in future enabling the res...

A review of morphological investigations carried out to clarify the pathogenicity of industrial dust produced in the mining and processing of Estonian oil shale is given. Histological examination of lungs of workers in the oil shale industry taken at necropsies showed that the inhalation of oil shale dust over a long period (more than 20 years) may cause the development of occupational pneumoco...