Data Processing and Knowledge Discovery in Databases

With advanced computer technologies and their omnipresent usage, data accumulates in a speed unmatchable by the human’s capacity of data processing. To meet this growing challenge, the community of knowledge discovery from databases emerged not long ago. The key issue studied by the community is, in a layman’s term, to make use of the data to our advantage. Or, why should we collect so much of it in the first place? In order to make the raw data useful, we need to represent it, process it, extract knowledge from it, present and understand knowledge for various applications. Through the first chapter, we provide the computational model of our study and the representation of data, and introduce the field of knowledge discovery from databases that evolves from many fields such as classification and clustering in statistics, pattern recognition, neural networks, machine learning, databases, exploratory data analysis, on-line analytical processing, optimization, high-performance and parallel computing, knowledge modeling, and data visualization. The ever advanced data processing technology and the increasing demand of taking advantages of data stored form a new challenge for data mining; one of the solutions to this new challenge is feature selection — the core of this study.

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