Research and development (R&D) for space science and technology applications (SSTA), specially for those directed towards outer space science, require large amount of resources, and high level of expertise. While the Philippine space program is relatively young, the Philippines have a number of excellent scientists and engineers who work on fields that are related to SSTA, referred to as space adjacent fields. Support for space adjacent R&D will push the Philippines further in the field of SSTA, and help us in our goal of creating value from space for Filipinos and the world. The team from PhilSA developed a machine learning tool using a method called k-nearest neighbor (kNN) that will classify research works produced in the Philippines into twelve space adjacent areas important to outer space SSTA. Results show that the tool developed in PhilSA is able to identify the R&D field that a paper belongs to within acceptable accuracy. This tool will help PhilSA as it plans its future activities together with Philippine scientists and engineers.
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