ComputingComputer ScienceInformation RetrievalRecommender SystemsText AnalyticsBibliometric AnalysisCollaborative FilteringEvaluation Of Recommender SystemsLiterature MiningRecommendation EvaluationRetrieval ModelsCitation RecommendationDocument RecommendationMetadata-based SearchResearch ArticlesScientific Knowledge ConstructionScientific Literature Mining
The body of scientific literature is growing at an exponential rate. This expansion of scientific knowledge has increased the need for tools to help users find relevant articles. However, researchers developing new scholarly article recommendation algorithms face two substantial hurdles: acquiring high-quality, large-scale scholarly metadata and mechanisms for evaluating their recommendation algorithms. To address these problems we created Babel---an open-source platform uniting publisher, researchers, and users. Babel includes tens of millions of scholarly articles, several recommendation algorithms, and tools for integrating recommendations into publisher websites and other scholarly platforms.
8
Bibliographic coupling between scientific papers
M. M. Kessler · American Documentation · 1963 · 2.8K citations
Jie Tang, Jing Zhang, Limin Yao et al. · 2008 · 2.1K citations
Research paper recommender system evaluation
Joeran Beel, Stefan Langer, Marcel Genzmehr et al. · 2013 · 158 citations