Human-centered text mining: a new software system

Authors:
Jonas Poelmans;Paul Elzinga;Alexei A. Neznanov;Guido Dedene;Stijn Viaene;Sergei O. Kuznetsov
Affiliations:
Faculty of Business and Economics, KU Leuven, Leuven, Belgium,National Research University Higher School of Economics (HSE), Moscow, Russia;Amsterdam-Amstelland Police, Amsterdam, The Netherlands;National Research University Higher School of Economics (HSE), Moscow, Russia;Faculty of Business and Economics, KU Leuven, Leuven, Belgium,Universiteit van Amsterdam Business School, Amsterdam, The Netherlands;Faculty of Business and Economics, KU Leuven, Leuven, Belgium,Vlerick Leuven Gent Management School, Leuven, Belgium;National Research University Higher School of Economics (HSE), Moscow, Russia
Venue:
ICDM'12 Proceedings of the 12th Industrial conference on Advances in Data Mining: applications and theoretical aspects
Year:
2012

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Abstract

In this paper we introduce a novel human-centered data mining software system which was designed to gain intelligence from unstructured textual data. The architecture takes its roots in several case studies which were a collaboration between the Amsterdam-Amstelland Police, GasthuisZusters Antwerpen (GZA) hospitals and KU Leuven. It is currently being implemented by bachelor and master students of Moscow Higher School of Economics. At the core of the system are concept lattices which can be used to interactively explore the data. They are combined with several other complementary statistical data analysis techniques such as Emergent Self Organizing Maps and Hidden Markov Models.