DMOLD-13: Data Mining on Linked Data Workshop and Challenge
The workshop consists of an Open Track and of a Challenge Track. The Challenge focuses Public Contract Procurement data, includes 3 tasks: prediction of the number of bidders; prediction of the type of contract; and unrestricted discovery of interesting nuggets of any sort
To be held during the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML/PKDD 2013, 23-27 September 2013 Prague, Czech Republic (www.ecmlpkdd2013.org)
The workshop consists of an Open Track and of a Challenge Track.
The Open Track will expect submission of regular research papers, describing novel approaches to applying Data Mining techniques on the Linked Data sources.
Participation in the Challenge Track will require the participants to download a Public Contract Procurement dataset, and accomplish at least one of the three pre-defined tasks.
- May 1, 2013 - Challenge Track data for Task 1 and Task 3
- May 15, 2013 - Challenge Track data for Task 2
- June 21, 2013 - Deadline for Challenge Track results
- June 28, 2013 - Deadline for paper submissions (both Open Track and of a Challenge Track)
The three challenge tasks are
- Task 1 concerns prediction of the number of bidders for the respective public contract; the true value of this target attribute will only be known after the bidding period has been closed.
- Task 2 concerns prediction of the type of contract in terms of 'sub-contract homogeneity' (so called multi-contract covering items of dissimilar kind; its opposite; or borderline case between the two); this 'soft' target class will be manually added to the data by a team of domain experts.
- Task 3 amounts to unrestricted discovery of interesting nuggets of any sort in the (augmented) dataset. The results will be evaluated for interestingness and novelty by domain experts; the most valuable results should be such those potentially igniting discussions on transparency or unexpected economic consequences of certain procurement segments.
The datasets used in LDMC will come from public contracts sources in United States and Great Britain.
For more info about the Challenge, visit keg.vse.cz/dmold2013
For more info about the ECML/PKDD 2013, visit www.ecmlpkdd2013.org
Claudia d'Amato, Petr Berka, Vojtech Svatek & Krzysztof Wecel