Heikki Mannila

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Heikki Mannila (born 1960)[1] is a Finnish computer scientist, the president of the Academy of Finland.

Mannila earned his Ph.D. in 1985 from the University of Helsinki under the supervision of Esko Ukkonen[2] and for many years he was a professor at the University of Helsinki himself. From 2004 to 2008 he was Academy Professor at the Academy of Finland. He became Vice President for Academic Affairs at Aalto University in 2009, and was appointed by the Finnish government as president of the Academy of Finland for a term lasting from 2012 to 2017.[1][3]

Mannila is known for his research in data mining, and has published highly cited papers on association rule learning[4] and sequence mining.[5] With David Hand and Padhraic Smyth, he is the co-author of the book Principles of Data Mining (MIT Press, 2001).[6]

References

  1. ↑ 1.0 1.1 Heikki Mannila appointed as President of the Academy of Finland, Finnish Ministry of Education and Culture, December 19, 2011, retrieved 2012-02-25.
  2. ↑ Mathematical genealogy of Heikki Mannila from the International Association for Cryptologic Research, retrieved 2012-02-25.
  3. ↑ Heikki Mannila takes office as President of the Academy of Finland, University of Helsinki Computer Science Department, retrieved 2012-02-25.
  4. ↑ Klemettinen, Mika; Mannila, Heikki; Ronkainen, Pirjo; Toivonen, Hannu; Verkamo, A. Inkeri (1994), "Finding interesting rules from large sets of discovered association rules", Proc. 3rd International Conf. Information and Knowledge Management, pp. 401–407, doi:10.1145/191246.191314 . Mannila, Heikki; Toivonen, Hannu; Verkamo, A. Inkeri (1994), "Efficient algorithms for discovering association rules", Proc. Worksh. Knowledge Discovery in Databases, pp. 181–192 . Agrawal, Rakesh; Mannila, Heikki; Srikant, Ramakrishnan; Toivonen, Hannu; Verkamo, A. Inkeri (1996), "Fast discovery of association rules", Advances in Knowledge Discovery and Data Mining, AAAI, pp. 307–328 .
  5. ↑ Mannila, Heikki; Toivonen, Hannu; Inkeri Verkamo, A. (1997), "Discovery of Frequent Episodes in Event Sequences", Data Min. Knowl. Discov. 1 (3): 259–289, doi:10.1023/A:1009748302351 .
  6. ↑ Review of Principles of Data Mining, Ashish P Sanil (2003), J. Amer. Stat. Assoc. 98 (461): 252–253, doi:10.1198/jasa.2003.s257.
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