Multiple-Objective Optimization for Library Journal Portfolios - A Machine Learning Approach
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Authors
Forrest, Jay
Issue Date
2025-11-13
Type
Presentation
Language
en_US
Keywords
Alternative Title
Abstract
While cost/use is a traditional analysis tool for evaluating Library Resources, for journals we have a richer data set including local citation rates and local authorship rates. Adding additional variables create a multiple object optimization problem. This presentation explores a machine learning technique, genetic algorithms, to explore solutions to this problem.