Best Student Paper Award @ ICWE2020 for Harm Delva

(23-06-2020) Best Student Paper Award @ ICWE2020 for Harm Delva

When fragmenting public transport timetables, it turns out the precise method for fragmenting the dataset does not matter much. You can thus go for a rather simple geo-spatial approach that is easy to implement. While the set-up of the research was to try to find the best clustering approach for this use case, the team at IDLab came up with a “negative” result and still decided to publish this paper. This was not in vain, as the honest evaluation of the paper turned into the Best Student Paper award for our PhD candidate Harm Delva! It would not be a paper from our lab if we also didn’t introduce the hypermedia controls we see fit for describing such clusters of public transport data for intelligent agents too of course. Link to the paper