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There is a great and urgent necessity for appropriate data and methods to help organisations select appropriate R&D (Research and Development) partners. In response, this study presents a structured framework for identifying and selecting the R&D partners with the greatest potential to meet a given technological need. The formal methods in the framework include systematic information collection, patent portfolio analysis, technological similarity screening, and semantic evaluation that views subject-action-object (SAO) sentence structures as problem-solution patterns. The results of an empirical evaluation, with dye-sensitive solar cells as the case, demonstrate that using this framework can reveal more appropriate R&D partners for technological needs (TNS) in less time and with less cost than methods based solely on one criterion.
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Stored only when both papers are in the corpus — 13 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.