Bisociative Knowledge Discovery: An Introduction to Concept, by Michael R. Berthold

By Michael R. Berthold

Sleek wisdom discovery equipment allow clients to find advanced styles of assorted varieties in huge info repositories. notwithstanding, the underlying assumption has consistently been that the information to which the tools are utilized to originates from one area. the point of interest of this ebook, and the BISON undertaking from which the contributions are originating, is a community established integration of assorted forms of info repositories and the improvement of latest how one can examine and discover the ensuing enormous details networks. rather than discovering good outlined international or neighborhood styles they desired to locate area bridging institutions that are, by way of definition, no longer good outlined due to the fact they are going to be specifically attention-grabbing in the event that they are sparse and feature now not been encountered earlier than. The 32 contributions offered during this state of the art quantity including an in depth creation to the booklet are equipped in topical sections on bisociation; illustration and community construction; community research; exploration; and purposes and evaluate.

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Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications

Glossy wisdom discovery tools permit clients to find complicated styles of varied forms in huge info repositories. although, the underlying assumption has constantly been that the information to which the tools are utilized to originates from one area. the focal point of this e-book, and the BISON undertaking from which the contributions are originating, is a community established integration of varied varieties of facts repositories and the improvement of recent how one can examine and discover the ensuing tremendous details networks.

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Extra resources for Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications

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Towards Creative Information Exploration Based on Koestler’s Concept 29 Computational Creativity in Science. Computational creativity [7] in art, music and poetry has been around for some time. A recent development is computational creativity applied to the fields of science and engineering. For example, the aim of the Symposium on Computational Approaches to Creativity in Science7 (Stanford, US, 2008) was to explore (among other things) (a) the role creativity plays in various scientific areas and how ICT-based tools could contribute to scientific tasks and processes, (b) the nature of creativity in search through a problem space and the representation of the search space and the problem description, (c) the role background knowledge plays in aiding and possibly interfering with creative processes in science, and (d) the interactions among scientists that increase creativity and how computational tools could support these interactions.

De Abstract. The integration of heterogeneous data from various domains without the need for prefiltering prepares the ground for bisociative knowledge discoveries where attempts are made to find unexpected relations across seemingly unrelated domains. Information networks, due to their flexible data structure, lend themselves perfectly to the integration of these heterogeneous data sources. This chapter provides an overview of different types of information networks and categorizes them by identifying several key properties of information units and relations which reflect the expressiveness and thus ability of an information network to model heterogeneous data from diverse domains.

Second, in contrast to bisociation, analogical reasoning seems to suggest a similar (analogous) structure of the long-term memory entity that is retrieved and the input case prompting the retrieval. Bisociation is more akin to Minsky’s concept of knowledge lines [26], which are a kind of “scaffold” attached to the “mental agencies” (facts, concepts, routines, habits, associations) that were active in creating a certain idea or solving a particular problem in the past. The knowledge lines later work as a way to re-activate the same structures in the context of a new problem.

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