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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.

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SISAP Indexing Challenge 2025 – Solution for Task 2 Using Root Join

  • 会议论文

  • 发表日期：

    2026年

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  • Benjamin Bustos,
  • Jiale Chen

摘要

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.