helsinki1.jpg

Finnish music sells worse in digital stores than in traditional shops

The Finnish music market‘s share is smaller in digital music stores than in traditional music shops. According to sales and consumption statistics, non-Finnish artists‘ share of all sold music grows when people buy music from the web and mobile stores instead of traditional record stores. The observation was published in a report on the recent trends in music consumption in Finland. The report was made by Helsinki Institute for Information Technology HIIT.

Finnish music sells worse in digital stores than in traditional shops

Tue, 27.04.2010

27 Apr 2010 - The Finnish music market‘s share is smaller in digital music stores than in traditional music shops. According to sales and consumption statistics, non-Finnish artists‘ share of all sold music grows when people buy music from the web and mobile stores instead of traditional record stores. The observation was published in a report on the recent trends in music consumption in Finland. The report was made by Helsinki Institute for Information Technology HIIT.

Kotimainen musiikki myy internetissä huonommin kuin levykaupoissa

Kotimaisen musiikin osuus myydyistä kappaleista on pienempi, kun ihmiset ostavat musiikkia internetin ja kännykän kautta levykauppojen sijaan. Digitaalisten tallenteiden myynti- ja kulutustilastoissa ulkomaalaisten artistien myyntiosuus kasvaa perinteisten levykauppojen hiljentyessä. Havainnot selviävät suomalaisen musiikkikulutuksen trendejä käsittelevästä raportista, jonka tiedot on koonnut Tietotekniikan tutkimuslaitos HIIT.

23 Apr 10:15 Juan Diego Rodríguez: Learning Bayesian network classifiers for multi-dimensional supervised classification problems by means of a multi-objective approach

HIIT seminar, Friday Apr 23, 10:15 a.m. (coffee from 10), Exactum B222

Juan Diego Rodríguez
Intelligent Systems Group, University of the Basque Country, Spain
Visiting Researcher at HIIT (Complex Systems Computation Group)

Learning Bayesian network classifiers for multi-dimensional supervised classification problems by means of a multi-objective approach

Honorable mention to Petri Kontkanen's Doctoral dissertation

Wed, 21.04.2010

21 Apr 2010 - Petri Kontkanen received an honorable mention for the second best PhD thesis in the shortlist for the Classification Society Distinguished Dissertation Award of 2010. The title of Dr. Kontkanen's dissertation is "Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering".

Pages