Increasing Papers' Discoverability with Precise Semantic Labeling: the sci.AI Platform
This addresses the issue of relevant publication retrieval for researchers in biomedicine, but it appears incremental as it builds on existing semantic labeling approaches.
The researchers tackled the problem of low discoverability of biomedical papers due to terminology variability and ambiguity, and they presented the sci.AI platform as a solution for precise semantic labeling to improve retrieval.
The number of published findings in biomedicine increases continually. At the same time, specifics of the domain's terminology complicates the task of relevant publications retrieval. In the current research, we investigate influence of terms' variability and ambiguity on a paper's likelihood of being retrieved. We obtained statistics that demonstrate significance of the issue and its challenges, followed by presenting the sci.AI platform, which allows precise terms labeling as a resolution.