Data Mining and Knowledge Management Laboratory

Research

The amount of data and text has increased considerably during the last ten years and we are already talking about a future data amount of peta (10¹⁵) or even yotta (10²⁴) bytes on the Internet. Today, many organizations struggle with vast amounts of data. Worldwide, computers have turned into massive data tombs. It is possible to capture and store data, but it has become difficult to utilize it effectively and efficiently.

The overall research goal is to search for, find, model and systemize/analyze knowledge in very large sets of data using data- and text mining, so that organizations can use this knowledge in decision making.

Systematizing knowledge using data and in particular text mining is new and demanding. Focus is on the following application areas

Financial benchmarking and performance analysis
Bankruptcy prediction
Corporate taxation and tax auditing
Customer segmentation
Market basket analysis
Modeling customers in electricity retailing markets
Monitoring financial stability
Electronic patient records

Other areas of interest are:

Customer participation in agile software development
End-user development support through the Web

Education based on research

Regular advanced courses in IS:

Data Mining and Text Mining, Autumn 2011
Business Intelligence, Autumn 2011

Research Unit Web Page: https://research.it.abo.fi/research/data-mining-and-knowledge-management-laboratory

Leader of the unit

Barbro Back

Co-leader of the unit

Tomas Eklund

Senior Researchers

Tomas Eklund Dorina Marghescu

Doctoral Students

Piia Hirkman Minna Kallio Henri Korvela Annika H. Holmblom Hongyan Liu Zhiyuan Yao Peter Sarlin Samuel Rönnqvist

Projects

Kermit

(Knowledge mining in organizations) 2009-2012. Total funding 363.000 euro. Academy of Finland.

UnHide

(BI for comptetitor analysis) 2009-2012. Total funding 195.450 euro. Academy of Finland

Titan

2008-2011. Total funding 400.000 euro. Tekes.

Publications

Click here to see the full list of publications from the TUCS Publication Database

The latest updated publications:

Peter Sarlin, Self-Organizing Time Map: An Abstraction of Temporal Multivariate Patterns. Neurocomputing 99(1), 496–508, 2013.

Peter Sarlin, On Policymakers’ Loss Functions and the Evaluation of Early Warning Systems. Economics Letters 119(1), 1–7, 2013.

Peter Sarlin, Exploiting the Self-Organizing Financial Stability Map. Engineering Applications of Artificial Intelligence 26(5), 1532–1539, 2013.

Peter Sarlin, A Weighted SOM for Classifying Data with Instance-Varying Importance. In: Jilles Vreeken, Charles Ling (Eds.), Proceedings of the IEEE 12th International Conference on Data Mining Workshops (ICDMW), 187–193 , IEEE, 2013.

Peter Sarlin, Mapping Financial Stability. TUCS Dissertations 159. 2013.

Hongyan Liu, Jüri Vain, An Agent-Based Modeling for Price-Responsive Demand Simulation. TUCS Technical Reports 1065, ISBN 978-952-12-2843-8, 2013.

Tomas Eklund, Petri Paajanen, Jussi Kantola, Hannu Vanharanta, Knowledge Creation and Learning in Organizations – Measuring Proactive Vision Using the Co-Evolute Methodology. International Journal of Strategic Change Management 4(2), 190–201, 2012.

Peter Sarlin, Visual Tracking of the Millennium Development Goals with a Fuzzified Self-Organizing Neural Network. International Journal of Machine Learning and Cybernetics 3(3), 233–245, 2012.

Peter Sarlin, Zhiyuan Yao, Tomas Eklund, A Framework for State Transitions on the Self-Organizing Map: Some Temporal Financial Applications. Intelligent Systems in Accounting, Finance and Management 19(1), 189–203, 2012.

Henri Korvela, Barbro Back, The Impact of Skills and Demographics on End-User Developers’ Use of Support. In: Len Jessup, Joe Valacich (Eds.), AMCIS 2012 Proceedings, End-user Information Systems, Innovation, and Change (SIGOSRA), 1–9, Association for Information Systems , 2012.

Hongyan Liu, Zhiyuan Yao, Tomas Eklund, Barbro Back, From Smart Meter Data to Pricing Intelligence – Visual Data-Mining towards Real-Time BI. In: K.D. Joshi, Youngjin Yoo (Eds.), AMCIS, 1–10, AISeL, 2012.

Hongyan Liu, Zhiyuan Yao, Tomas Eklund, Barbro Back, Electricity Consumption Time Series Profiling: A Data Mining Application in Energy Industry. In: Petra Perner (Ed.), Advances in Data Mining: Applications and Theoretical Aspects, LNAI 7377, 52–66, Springer, 2012.

Henrik J. Nyman, Piia Hirkman, On the Nature of Supply Chain Management Projects and how to Manage Them. In: J. Pries-Heje, M. Chiasson (Eds.), ECIS 2012 Proceedings, 1–12, AISeL, 2012.

Peter Sarlin, On Biologically Inspired Predictions of the Global Financial Crisis. In: Klaus G. Troitzsch, Michael Möhring, Ulf Lotzmann (Eds.), Proceedings of the 26th European Conference on Modelling and Simulation, 253–259, European Council for Modelling and Simulation, 2012.

Peter Sarlin, Decomposing the Global Financial Crisis: A Self-Organizing Time Map. In: Manuel Graña, Carlos Toro, Jorge Posada, Robert Howlett, Lakhmi Jain (Eds.), Proceedings of the 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES'12), 798–806, IOS Press, 2012.

Peter Sarlin, Exploiting the Self-Organizing Financial Stability Map. In: Manuel Graña, Carlos Toro, Jorge Posada, Robert Howlett, Lakhmi Jain (Eds.), Proceedings of the 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES'12), 248–257, IOS Press, 2012.

Peter Sarlin, Zhiyuan Yao, Tomas Eklund, Probabilistic Modeling of State Transitions on the Self-Organizing Map: Some Temporal Financial Applications. In: Ralph H. Jr. Sprague (Ed.), Proceedings of the 45th Hawaii International Conference on System Sciences, 1128-1137, IEEE Press, 2012.

Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back, Combining Visual Customer Segmentation and Response Modelling. In: ECIS 2012 Proceedings, 1–10, AIS Electronic Library (AISeL), 2012.

Zhiyuan Yao, Peter Sarlin, Tomas Eklund, Barbro Back, Temporal Customer Segmentation Using the Self-Organizing Time Map. In: Ebad Banissi, Stefan Bertschi, Camilla Forsell, Jimmy Johansson, Sarah Kenderdine, Francis T. Marchese, Muhammad Sarfraz, Liz Stuart, Anna Ursyn, Theodor G. Wyeld, Hanane Azzag, Mustapha Lebba, G. Venturini (Eds.), Proceedings of the 2012 16th International Conference on Information Visualisation (IV), 234–240, IEEE Press, 2012.

Hongyan Liu, Tomas Eklund, Barbro Back, Smart Metering and Customer Consumption Behavior Profiling: Exploring Potential Business Opportunities for DSOs and Electricity Retailers. In: Jussi Kantola, Waldemar Karwowski (Eds.), Knowledge Service Engineering Handbook, Page 179-189, Taylor & Francis, 2012.

Peter Sarlin, Chance Discovery with Self-Organizing Maps: Discovering Imbalances in Financial Networks. In: Yukio Ohsawa, Akinori Abe (Eds.), Advances in Chance Discovery, 49–61, Springer, 2012.

Hannu Vanharanta, Camilla Magnusson, Kari Ingman, Annika H. Holmbom, Jussi Kantola, Strategic Knowledge Services. In: Jussi Kantola, Waldemar Karwowski (Eds.), Knowledge Service Engineering Handbook, 529-557, CRC Press, Taylor and Francis Group, 2012.

Hongyan Liu, Zhiyuan Yao, Thomas Eklund, Barbro Back, From Smart Meter Data to Pricing Intelligence: Real Time BI for Business Innovation. TUCS Technical Reports 1035, Turku Centre for Computer Science, 2012.

Peter Sarlin, Data and Dimension Reduction for Visual Financial Performance Analysis. TUCS Technical Reports 1049, TUCS, 2012.

Peter Sarlin, On Policymakers' Loss Functions and the Evaluation of Early Warning Systems. TUCS Technical Reports 1054, TUCS, 2012.

Peter Sarlin, A Weighted SOM for Classifying Data with Instance-Varying Importance. TUCS Technical Reports 1060, TUCS, 2012.

Peter Sarlin, Zhiyuan Yao, Clustering of the Self-Organizing Time Map. TUCS Technical Reports 1062, TUCS, 2012.

Where academic tradition meets the exciting future