Description
The Esploro research information management solution optimizes data completeness, quality, and cost. Esploro repurposes existing data (e.g., from FAR systems), utilizes our Central Discovery Index (CDI) database to enhance metadata, and employs Smart Harvesting — a machine learning algorithm — to find additional publications in CDI on an ongoing basis. The data are then available in an open, accessible manner to serve many use cases at the institution, such as populating profiles and CVs, locating subject matter experts, indexing in Google Scholar, prepopulating annual review packets, reporting and analysis, and integrating into other systems through APIs and open standards.
Event Website
https://expertfindersystems.org/program.cfm
Start Date
6-4-2023 4:00 PM
End Date
6-4-2023 5:00 PM
Recommended Citation
Branch, Sarah and Horon, Jeff, "A Smarter Approach to the Expert Finder System Profile Completeness-Quality-Cost Tradeoff" (2023). International Forum on Expert Finder Systems. 1.
https://efsrimsrepository.expertfindersystems.org/efs_forum/2023/posters/1
A Smarter Approach to the Expert Finder System Profile Completeness-Quality-Cost Tradeoff
The Esploro research information management solution optimizes data completeness, quality, and cost. Esploro repurposes existing data (e.g., from FAR systems), utilizes our Central Discovery Index (CDI) database to enhance metadata, and employs Smart Harvesting — a machine learning algorithm — to find additional publications in CDI on an ongoing basis. The data are then available in an open, accessible manner to serve many use cases at the institution, such as populating profiles and CVs, locating subject matter experts, indexing in Google Scholar, prepopulating annual review packets, reporting and analysis, and integrating into other systems through APIs and open standards.
https://efsrimsrepository.expertfindersystems.org/efs_forum/2023/posters/1
Comments
This is a poster presentation from the 2023 EFS Conference.