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  3. Intuitive Knowledge Connectivity Intuitive Knowledge Connectivity

Intuitive Knowledge Connectivity

User knowledge interaction and autonomic knowledge technologies for a cloud-based distributed knowledge representation.

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

15.08.2015 - 31.08.2016

Overview

Data is produced in big volume, velocity and variety. Despite many research initiatives in big data analytics, individual users are still overwhelmed with a flood of data. Current big data strategies focus mainly on organizational uses of data analytics. In contrast, the long-term vision of this project is to assists individuals in coping with big data using an artificially intelligent digital assistant. Dealing with information overload is a personal connective learning process. Therefore, we envision a software that enables individuals to connect new relevant data to an existing distributed but integrated cloud-based knowledge structure semi-automatically. The goal of this small project is to establish a software framework that makes manifest the concept of a personal knowledge warehouse based on knowledge connectivity. This project has two deliverables: (1) a small software prototype that demonstrates the key concepts from an engineering perspective, and (2) a scientific publication that defines possible answers to the research questions from a scientific perspective. This will help establish funding for a larger project that focuses on user experience.

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Facts

Type of project

Forschung

Internal organisations involved
  • CC Distributed Secure Software Systems
  • Data Intelligence F&E
External project partner
  • Universität Bern - Institut für Wirtschaftsinformatik
Funding
  • Private / Stiftungen
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Persons involved: internal

Project manager
  • Michael Kaufmann
Member of project team
  • Derek Fagan

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

08/15/2015 - 08/31/2016

Project Head

Prof. Dr. Michael Kaufmann

Lecturer

+41 41 757 68 48

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