Data Mining: Theory and Applications

Team

The team of Academy Prof. Heikki Mannila consists of 3 senior members (Mannila, Aristides Gionis, Jaakko Hollmén), 10 postdocs and 10 Ph.D. students. The background of the team is in algorithms and data mining. The main research emphasis is on sequence analysis (e.g., finding orders and segmentation), mining complex and heterogeneous data, especially pattern discovery, and structure discovery in high-dimensional data sets. The team has strong ties to application groups in gene mapping and genome structure, environmental sciences, linguistics, and telecommunications.

The page of the subgroup in Otaniemi.

Senior members

Academy Professor Heikki Mannila University of Helsinki and Helsinki Univesity of Technology
Dr. Jaakko Hollmén
Dr. Aristides Gionis

Background

Heikki Mannila's group focuses on data mining. Mannila has introduced and analyzed several central data mining concepts, including the problem of finding integrity constraints from databases. With Professor Hannu Toivonen he studied association rules and introduced the problem of finding episodes from sequences. Episodes have been applied to telecommunications and to medical genetics. Recently, Mannila's group has defined the concepts of recurrent sources in sequences and studied the problem of finding orders from unordered data. Heikki Mannila received the ACM SIGKDD Innovation award in 2003. He coauthored the book Principles of Data Mining with David Hand and Padhraic Smyth (MIT Press 2001). Mannila also has wide industrial experience from Microsoft Research (Redmond, USA) and Nokia Research Centre.u

Selected publications

• H. Mannila, H. Toivonen and I. Verkamo: Discovery of frequent episodes in event sequences. Data Mining and Knowledge Discovery, 1,3 (1997), 259-289.

• H. Toivonen, K. Vasko, H. Mannila, A. Korhola and H. Olander: Applying Bayesian statistics to organism-based environmental reconstruction. Ecological Applications, 11, 2, 618-630, 2001.

• H. Toivonen, P. Onkamo, K. Vasko, V. Ollikainen, P. Sevon, H. Mannila, M. Herr, and J. Kere. Data mining applied to linkage disequilibrium mapping. American Journal of Human Genetics} 67(1): 133 - 145, July 2000.

• J. Han, Russ B. Altman, V. Kumar, H. Mannila, and D. Pregibon: Emerging scientific applications in data mining. Communications of the ACM 45, 8 (August 2002), 54-58.

• D. Pavlov, H. Mannila, and P. Smyth: Beyond independence: probabilistic methods for query approximation on binary transaction data. IEEE Transactions on Data and Knowledge Engineering 15, 6 (2003), 1409-1421.

• M. Fortelius, A. Gionis, J. Jernvall, H. Mannila: Spectral Ordering and Biochronology of European Fossil Mammals. Paleobiology 32, 2, 206-214 (2006).

• K. Puolamäki, M. Fortelius, H. Mannila: Seriation in paleontological data using Markov Chain Monte Carlo methods. PLoS Computational Biology, e6, February 2006.

• A. Gionis, H. Mannila, T. Mielikäinen, P. Tsaparas: Assessing Data Mining Results via Swap Randomization. KDD 2006, Proceedings of the Twelth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, L Unger, M. Craven, D. Gunopulos, T. Eliassi-Rad (eds.), p. 167-176. (Runner-up, KDD Best Paper award.)

• P. Miettinen, T. Mielikäinen, A. Gionis, G. Das, H. Mannila: The Discrete Basis Problem. 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) 2006, to appear. (PKDD Best Paper.)

• S. Myllykangas, J. Himberg, T. Böhling, B. Nagy, J. Hollmén, and S. Knuutila: DNA copy number amplification profiling of human neoplasms. Oncogene. In press.

• M. Sulkava, J. Tikka, and J. Hollmén: Sparse regression for analyzing the development of foliar nutrient concentrations in coniferous trees. Ecological Modeling, 191(1):118-130, January 2006.

• H.J. Tikka, A. Lendasse, and J. Hollmén: Analysis of fast input selection: Application in time series prediction. In Stefanos Kollias, Andreas Stafylopatis, Wlodzislaw Duch, and Erkki Oja, editors, Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN'06), volume 4132 of Lecture Notes in Computer Science, pages 161-170. Springer-Verlag, 2006.