We present a solution for Task 2 of the SISAP Indexing Challenge 2025. The task
consists of building the k-NN graph (self-similarity join) under limited memory
and storage resources. Our solution is based on an approximate algorithm called
Root Join, which we combine with some pre-processing steps to improve its
performance with large high-dimensional data. For the specific task, we require
building the k-NN graph for k = 15 with vectors of 384-D and the dataset has a
size of approximately 3 million vectors. Our solution is focused on working
under the restricted execution conditions of the Challenge, which consists of:
a Linux container with 8 virtual CPUs, 16GB of RAM, and a time limit of 12 h.