My current research interests mainly concern applications of machine learning in the context of natural language processing / understanding.
At the moment I am also a visiting scientist at Speechly working on NLU stuff.
Here you can find reference implementations of some algorithms I've worked on, and datasets used in some of my papers.
Triplet data that we collected for the experiments in (Heikinheimo & Ukkonen, HCOMP 2013) is available here. Please see the README file for instructions. If you use this in your research, I am kindly asking you to cite our HCOMP 2013 paper.
Spectra is an algorithm for quickly estimating the "pattern frequency spectrum" of a binary dataset. This is a curve that shows the number of frequent itemsets for a given support threshold.
Fast-Skyline is an algorithm for computing approximate “skylines” (non-dominated sets) of subsets of size-k subject to two functions, one linear, one submodular. That is, the algorithm computes the set of non-dominated subsets of size-k. This problem has applications in e.g. viral marketing.
Antti Ukkonen, Academy Research Fellow
Department of Computer Science
University of Helsinki
antti.ukkonen (at) helsinki.fi (for work related matters)
antti.ukkonen (at) gmail.com (for other business)
My LinkedIn page