SciBite, an Elsevier semantic technology company, announced the launch of SciBiteSearch, a scientific search and analytics platform that offers interrogation and analysis capabilities across unstructured and structured data, from public and proprietary sources. SciBiteSearch provides scientists with access to domain specific ontology and AI-powered search capabilities.
SciBiteSearch uses knowledge graphs to augment searches and deliver not only items relevant to the query but the structure and relationship between them. The addition of AI enables natural language understanding. SciBiteSearch can integrate data across a range of use cases including:
- Unify multiple data sources into a single solution, designed for departments wanting their own tailored search tool. For example, combining public biomedical literature, clinical trials, and grants with proprietary data.
- Incorporate full-text biomedical literature from publishers to better address researchers’ discovery needs. For example, users can load subscribed licensed data from partner publishers or content brokers.
- Enable users to get accurate search results without the need to understand the complexities of Named Entity Recognition (NER), its underlying data structures, or the functions required to surface.
SciBiteSearch creates sophisticated query and assertion indices created using SciBite’s tools and ontologies. A streaming load API, connectors, and parsers for different sources and content types let it load and process content to make it searchable.