Sebastián Martins

Deriving Processes of Information Mining Based on Semantic Nets and Frames

There are information mining methodologies that emphasize the importance of planning for requirements elicitation along the entire project in an orderly, documented, consistent and traceable manner. However, given the characteristics of this type of project, the approach proposed by the classical requirements engineering is not applicable to the process of identifying the problem of information mining, nor allows to infer from the business domain modelling, the information mining process which solves it. This paper proposes an extension of semantic nets and frames to represent knowledge of the business domain, business problem and problem of information mining; and a methodology to derive the information mining process from the proposed knowledge representations is introduced.

Intelligent Systems in Modeling Phase of Information Mining Development Process

The Information Mining Engineering (IME) understands in processes, methodologies, tasks and techniques used to: organize, control and manage the task of finding knowledge patterns in information bases. A relevant task is selecting the data mining algorithms to use, which it is left to the expertise of the information mining engineer, developing it in a non-structured way. In this paper we propose an Information Mining Project Development Process Model (D-MoProPEI) which provides an integrated view in the selection of Information Mining Processes Based on Intelligent Systems (IMPbIS) within the Modeling Phase of the proposed Process Model through a Systematic Deriving Methodology.

Information Mining Projects Management Process

Information Mining (also known as Knowledge Discovery Process) is a growing discipline in continuous expansion. Most of the progress accomplished, are focus on the development activities (i.e. those technical activities associated with the comprehension and adaptation of data, and the implementation of data mining algorithm). According to this conceptual framework, several process models were developed, which allow organizing and defining the set of tasks related to the development of information mining projects. These approaches omit the set of tasks oriented to the management and control of the process. In this paper, we propose a transversal management process to the development process currently in use in information mining projects. The proposed process focuses on removing existing gaps, providing an improvement on the projects maturity and quality levels.