During our 2nd Critical Space with guest expert Bob Sturm (KTH Royal Institute of Technology, Stockholm, Sweden) we presented and discussed a first mock-up of our “GO CURATOR” idea.
Here you can see DAD team members setting up the physical model.
GO CURATOR analyses text describing paintings in museum collections. Topic modelling is used to represent the semantic content in these texts, thereby targeting the semantic meaning of the paintings themselves.
Result is a probabilistic distribution across topics for every painting. E.g. in the painting below, the topics “food”, “act”, “human” and “object” are present to an equal extent of 25%.
Curators or museum visitors can change the exhibition interactively by adjusting which topics should be present to what extent. GO CURATOR then automatically adjusts the choice of paintings and their exact hanging in the museum room.