Knowledge discovery generally focuses on finding patterns within a reasonably well connected domain of interest. In this article we outline a framework for the discovery of new connections between domains (so called bisociations), supporting the creative discovery process in a more powerful way. We motivate this approach, show the difference to classical data analysis and conclude by describing a number of different types of domain-crossing connections. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Berthold, M. R. (2012). Towards bisociative knowledge discovery. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7250, 1–10. https://doi.org/10.1007/978-3-642-31830-6_1
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