IADIS International Journal on Computer Science and Information Systems

Published by IADIS (International Association for Development of the Information Society) • ISSN (Online): 1646-3692 • ISSN (Print): 1646-3692
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Dynamic Identification by Enumeration for Co-operative Knowledge Discovery

Oksana Arnold *
Sebastian Drefahl *
Jun Fujima *
Klaus P. Jantke *
Christoph Vogler *
* 1Erfurt University of Applied Sciences. Altonaer Str. 25, 99085 Erfurt, Germany 2ADICOM Software. Frauentorstr. 11, 99423 Weimar, Germany 3National Inst. for Materials Science. 1–2-1 Sengen, Tsukuba, Ibaraki 305–0047, Japan (Portugal)
* 1Erfurt University of Applied Sciences. Altonaer Str. 25, 99085 Erfurt, Germany 2ADICOM Software. Frauentorstr. 11, 99423 Weimar, Germany 3National Inst. for Materials Science. 1–2-1 Sengen, Tsukuba, Ibaraki 305–0047, Japan (Portugal)
* 1Erfurt University of Applied Sciences. Altonaer Str. 25, 99085 Erfurt, Germany 2ADICOM Software. Frauentorstr. 11, 99423 Weimar, Germany 3National Inst. for Materials Science. 1–2-1 Sengen, Tsukuba, Ibaraki 305–0047, Japan (Portugal)
* 1Erfurt University of Applied Sciences. Altonaer Str. 25, 99085 Erfurt, Germany 2ADICOM Software. Frauentorstr. 11, 99423 Weimar, Germany 3National Inst. for Materials Science. 1–2-1 Sengen, Tsukuba, Ibaraki 305–0047, Japan (Portugal)
* 1Erfurt University of Applied Sciences. Altonaer Str. 25, 99085 Erfurt, Germany 2ADICOM Software. Frauentorstr. 11, 99423 Weimar, Germany 3National Inst. for Materials Science. 1–2-1 Sengen, Tsukuba, Ibaraki 305–0047, Japan (Portugal)

Abstract

In contemporary information and communication technolo gies, there is an urgent need for transforming tools into assistant systems. Humans do not need more digital tools that require learning how to wield them, but digital assistants guiding them to unforeseeably valuable results – an effect named serendipity. This applies particularly when dealing with wicked prob lems which change over time when being tackled. Data analysis, visualization, and exploration is a characteristic domain of this type , particularly when open data are in focus, because the analysts have no background knowledge about the origin of these open data. The paper demonstrates the t ransformation of a tool for data analysis into an intelligent adaptive assistant. The transformation is based on the exploitation of concepts, methods, and technologies from disciplines such as meme media technology, natural language processing, and theory of mind modeling and induction. In comparison to earlier approaches to computational theory of mind induction, the present one relies on dynamically generated spaces of hypotheses. A rigorous mathematical proof demonstrates the superiority of the novel reasoning technology. A case study in business intelligence serves as proof of concept.

Keywords

Data Analysis Data Visualization Data Exploration Assistant Systems Intellige nt System Assistance Knowledge Discovery Meme Media Natural Language Processing Inductive Inference Theory of Mind Theory Induction 1
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Declarations & Ethics

Funding: This research received academic dissemination support through ESCAP / JournalsHub publishing programs.
Conflicts of Interest: The authors declare no competing financial or institutional interests.
Peer Review: Double-blind peer reviewed by international subject specialists.
License: Creative Commons Attribution 4.0 International (CC BY 4.0).
How to Cite This Article
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Arnold, et al. (2017). Dynamic Identification by Enumeration for Co-operative Knowledge Discovery. IADIS International Journal on Computer Science and Information Systems, 12(2). https://doi.org/10.33965/ijcsis_2017_v12i2_06
Arnold, et al. "Dynamic Identification by Enumeration for Co-operative Knowledge Discovery." IADIS International Journal on Computer Science and Information Systems, vol. 12, no. 2, 2017. https://doi.org/10.33965/ijcsis_2017_v12i2_06
Arnold, et al. "Dynamic Identification by Enumeration for Co-operative Knowledge Discovery." IADIS International Journal on Computer Science and Information Systems 12, no. 2 (2017). https://doi.org/10.33965/ijcsis_2017_v12i2_06