Use of HDBSCAN clustering to visualize the multi-dimensional public good space into well-defined groups of related projects in two dimensions.
Step 1: PRE-PROCESSING - embd.py creates embeddings of project descriptions Step 2: CLUSTERING - cluster.py reduces dimensionality using t-SNE and applies HDBSCAN for clustering
Sample results: Here are some algorithmically determined organic groupings of projects (a) saving water bodies, (b) protecting forests, (c) utilizing solar power, respectively
