Problem Solving in Data-Intensive Knowledge Discovery

M. Atkinson, R. Baxter, P. Brezany, O. Corcho, M. Galea, M. Parsons, D. Snelling, Jano van Hemert

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract / Description of output

This chapter aims at providing data analysis experts with an overview of the most common strategies in knowledge discovery, highlighting those steps or blocks of steps that are most likely to appear in common problem solving in conventional and data-intensive contexts, as well as giving examples that can be replicated in a range of problems in different domains. The chapter provides the common substrate that data analysis experts must know in order to address systematically their knowledge discovery problems in a data-intensive context. Inexperienced data analysis experts find the chapter useful for understanding and systematizing knowledge discovery, problem-solving procedures beyond individual steps and components for conventional to data-intensive problems. More experienced data analysis experts find the chapter useful to develop their understanding of how the data-intensive context influences conventional data analysis strategies.
Original languageEnglish
Title of host publicationThe Data Bonanza:Improving Knowledge Discovery in Science, Engineering, and Business
PublisherWiley-IEEE Computer Seciety Press
Pages147-163
Number of pages17
ISBN (Print)9781118540343
DOIs
Publication statusPublished - 2013

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