Multi-dimensional Information Ordering to Support Decision-making Processes

S. Marchand-Maillet, B. Hofreiter:
"Multi-dimensional Information Ordering to Support Decision-making Processes";
Vortrag: The 15th IEEE Conference on Business Informatics (CBI), Vienna; 15.07.2013 - 18.07.2013; in:"15th IEEE Conference on Business Informatics", IEEE, (2013), ISBN: 978-0-7695-5072-5; 8 S.

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Abstract:


Massive amounts of textual and digital data are
created daily from business or public activities. The organisation,
mining and summarization of such a rich and large
information source is required to capture the essential and
critical knowledge it contains. Such a mining is of strategic
importance in many domains including innovation (eg to mine
technological reviews and scientific literature) and electronic
commerce (eg to mine customer reviews).
Information content generally bears several important aspects,
mapped onto visualisation dimensions, whose number
needs to be reduced to enable relevant interactive exploration.
In this paper, we propose a novel strategy to mine and organise
document sets, in order to present them in a consistent manner
and to highlight interesting and relevant information patterns
they contain.
We base our method on the formulation of a global optimisation
problem solved by using the Traveling Salesman Problem
(TSP) approach. We show how this compact formulation opens
interesting possibilities for the mining of document collections
mapped onto multi-dimensional information sets. We discuss
the issue of scalability and show that associated scalable
solutions exist. We demonstrate the effectiveness of our method
over several types of documents, embedded into real business
cases.