Adaptive data communication interface: a user-centric visual data interpretation framework

Figueredo, Grazziela P., Wagner, Christian, Garibaldi, Jonathan M. and Aickelin, Uwe (2015) Adaptive data communication interface: a user-centric visual data interpretation framework. In: 9th IEEE International Conference on Big Data Science and Engineering (IEEE BigDataSE-15), 20-22 August 2015, Helsinki, Finland.

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Abstract

In this position paper, we present ideas about creating a next generation framework towards an adaptive interface for data communication and visualisation systems. Our objective is to develop a system that accepts large data sets as inputs and provides user-centric, meaningful visual information to assist owners to make sense of their data collection. The proposed framework comprises four stages: (i) the knowledge base compilation, where we search and collect existing state-of-the-art visualisation techniques per domain and user preferences; (ii) the development of the learning and inference system, where we apply artificial intelligence techniques to learn, predict and recommend new graphic interpretations (iii) results evaluation; and (iv) reinforcement and adaptation, where valid outputs are stored in our knowledge base and the system is iteratively tuned to address new demands. These stages, as well as our overall vision, limitations and possible challenges are introduced in this article. We also discuss further extensions of this framework for other knowledge discovery tasks.

Item Type: Conference or Workshop Item (Paper)
RIS ID: https://nottingham-repository.worktribe.com/output/988185
Additional Information: Due to be published IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Aickelin, Professor Uwe
Date Deposited: 14 Oct 2015 09:58
Last Modified: 04 May 2020 20:10
URI: https://eprints.nottingham.ac.uk/id/eprint/30453

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