Semantic Scholar is a free, AI-powered academic search engine and research tool developed by the Allen Institute for AI (AI2). Launched in 2015, the platform indexes over 200 million academic papers across all fields of science, including computer science, biomedical sciences, physics, mathematics, social sciences, and humanities, sourced from publishers, preprint servers, and open access repositories. Semantic Scholar uses natural language processing and machine learning to understand the content and context of academic papers, enabling more intelligent search and discovery than traditional keyword-based academic databases. The platform's key AI features include TLDR summaries that provide one-sentence AI-generated overviews of paper content, semantic search that understands the meaning behind queries to surface relevant papers even when they use different terminology, and citation context analysis that shows how a paper has been cited and in what context by subsequent research. Semantic Scholar also provides the Semantic Reader, an augmented reading interface that enhances the paper reading experience with inline definitions, citation cards, and figure references. The platform generates author profiles with publication histories, citation metrics, h-index calculations, and co-author networks. Its Research Feed feature uses machine learning to recommend new papers based on a user's research interests and reading history. Semantic Scholar offers the Semantic Scholar Academic Graph API, one of the largest open academic knowledge graphs, which researchers and developers can use to build applications on top of the platform's data. The platform is entirely free to use, supported by the Allen Institute for AI as part of its mission to advance AI for the common good. There are no premium tiers or paywalls for any of Semantic Scholar's features.
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