Molecular Connections collaborated with a leading scientific publishing society in the physical sciences to enhance content discoverability and recommendation. The project involved developing a rich ontology and semantically enriching millions of backfiles using AI/ML-driven solutions, including semantic fingerprinting and content classification.
Benefits & outcomes
- Improved content discoverability and recommendation.
- Real-time indexing of articles.
- Expansion of reviewer database, including authors, editors, and referees.
- Contextual advertising opportunities through thesaurus-driven ad space.
- Completion of the project in less than 6 months.
Notes & quotes
“The MC team ensured the ontology built was a manifestation of AIPP’s content.”
“Embracing the challenge of curating 1,500,000 terms and distilling them down to 35,000 terms across 26,000 topics.”
“The solution provided polyhierarchical support and semantically indexed 1 million articles with high accuracy.”
“The client witnessed improved discoverability and content recommendation, real-time indexing, an expanding reviewer database… and contextual advertising specific to selling thesaurus-driven ad space.”
Publisher / company: Molecular Connections
Date of case study: 01/01/2025
Source: https://mcpublishing.co.in/case_studies/improving-content-discovery-using-semantic-fingerprinting-and-machine-learning/