arXiv:2204.06142v2 Announce Type: replace-cross Abstract: Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources of experts and scholars, and these talents with great scientific and technological innovation ability are an important force to promote industrial upgrading. The scientific and technological resources of experts and scholars are mainly composed of basic attributes and scientific research achievements. The basic attributes include information such as research interests, institutions, and educationa
The proliferation of scientific knowledge and the increasing demand for efficient research resource management are driving this focus on automated retrieval systems.
Improving the discoverability and utilization of expert knowledge and research output can significantly accelerate innovation and industrial upgrading within scientific and technological sectors.
The efficiency with which institutions can leverage their internal human and intellectual capital through advanced retrieval mechanisms will improve, potentially leading to faster R&D cycles.
- · Academic institutions
- · Research institutes
- · R&D-intensive industries
- · AI/ML companies specializing in knowledge management
- · Organizations relying on manual or inefficient knowledge discovery
- · Traditional information gatekeepers
Scientific and technological resource utilization becomes more efficient through AI-driven retrieval systems.
Enhanced knowledge sharing and collaboration across expert networks could accelerate scientific breakthroughs and industrial applications.
Nations that effectively implement such systems could gain a competitive advantage in global innovation and economic development.
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Read at arXiv cs.AI