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For a researcher in a field of great industrial relevance, retrieving and analyzing research papers and patents has become an important aspect of assessing the scope of the field. We propose a method for creating a technical trend map automatically from both research papers and patents. For the construction of the technical trend map, we focus on the elemental (underlying) technologies used in a particular field, and their effects. Knowledge of the history and effects of the elemental technologies used in a particular field is essential for grasping the outline of technical trends in the field. Therefore, we have constructed a method that can recognize the application of elemental technologies and their effects in any research field. To investigate the effectiveness of our method, we conducted an experiment using the data in the NTCIR-8 Patent Mining Task. From our experimental results, we obtained Recall and Precision scores of 0.160 and 0.491, respectively, for the analysis of research papers. We also obtained Recall and Precision scores of 0.431 and 0.545, respectively, for the analysis of patents. Finally, we have constructed a system that creates an effective technical trend map for a given field.
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Stored only when both papers are in the corpus — 11 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.