Procedural Content Generation methods enable the creation of varied content algorithmically. Wave Function Collapse (WFC) is one such method. It is a tile-based local constraint solver commonly applied to world and map generation for grid-based content; it is able to create varied output from the same set of rules. While WFC is versatile, content generated with it is i) limited to one grid, ii) based on uniform tiles and iii) must use the same tile set and constraints throughout the grid. Due to these limitations, large classes of content are excluded, such as structured objects. Structured objects consist of an assembly of multiple components, each possibly based on a different tile set. We therefore propose Expressive Wave Function Collapse (XWFC), a major extension of WFC that enables solving and combining multiple grids with different Non-Uniform Tile (NUT) sets. Additionally, we can guarantee NUT shape and size preservation even under WFC’s Overlapping Model. With these generalizations, new domains are within reach for structured objects based on NUT sets, such as Tetris or LEGO.

Rotterdam Werkt! is a network of fourteen organizations in the Rotterdam area in the Netherlands. Their goal is to increase labor mobility between these organizations through sharing vacancies, exchanging employees and partaking in joint projects. Rotterdam Werkt! has tasked us with creating a central platform on which all vacancies are automatically combined from the websites of all the organizations in the network. The two main challenges of the project were to gather the vacancies from all the organizations affiliated with Rotterdam Werkt! and allow their recruiters to search and filter through them. This meant that a significant amount of research needed to be done in order to find a suitable scraping tool as well as a suitable search engine. Whilst gathering the vacancies, we ran into the problem that each website was significantly different in the way it is rendered. Furthermore, we also needed to categorize the data correctly such that it becomes searchable in the search engine. Lastly, the retrieval function needed to be optimized such that the most relevant vacancies would be returned for a given query. In order to assess whether recruiters could use the search engine effectively in practice, an evaluation of the effectiveness of the search engine was done. Three retrieval functions were compared based on a significance test of several effectiveness measures that indicate to what extent a retrieval function is able to retrieve relevant documents, or in this case, vacancies. Out of the three, the retrieval function that scored the highest was chosen to be used in the platform, so that recruiters will have a bigger chance to find the vacancies they will be looking for. In the end, we consider our project to be a success. We managed to scrape all vacancies from all the websites of the organizations in Rotterdam Werkt! and to combine these on a centralized platform. Furthermore, the search engine evaluation allowed us to select the best vacancy retrieval function out of the three evaluated retrieval functions. However, more work can still be put into evaluating the search engine in the future by testing more retrieval functions based on more vacancy data, so that the search functionality can be further improved.