Generally, a search tool optimized for a specific domain or a subject is unlikely to work well when applied to another domain or a subject. This inability to perform optimally across multiple disciplines or topics limits the utility of the search tool for scientific search. A way to overcome this challenge is by taking a semantic search approach.
Semantic search is a cluster of techniques that enable the algorithms of a search utility to probe a dataset for concept correlations and subsequently draw reliable inferences about hidden relationships lurking in the text. Using semantic techniques, relevant results can quickly be surfaced when the datasets include predefined scientific concepts.
Furthermore, incorporating semantic search in a search tool offers other possibilities such as better-targeted concept searching and e-discovery across scientific domains.