Semantic Scholar

Semantic Scholar Overview and Features - Semantic Scholar is a search engine for scientific research papers. - It provides a one-sentence summary of scientific literature. - It addresses the challenge of reading numerous titles and lengthy abstracts on mobile devices. - The project uses artificial intelligence to generate summaries through an abstractive technique. - Machine learning, natural language processing, and machine vision are used to add semantic analysis to citation analysis. - Research Feeds is an AI-powered feature that recommends the latest research to users. Number of Users and Publications - The Semantic Scholar corpus includes over 40 million papers from computer science and biomedicine. - The number of included papers metadata has grown to over 173 million after the addition of Microsoft Academic Graph records. - A partnership with the University of Chicago Press Journals made all articles published under the University of Chicago Press available in the corpus. - Semantic Scholar had indexed 190 million papers by the end of 2020. - It reached seven million users per month in 2020. AI2's Involvement in Semantic Scholar - AI2, the Allen Institute for Artificial Intelligence, is involved with Semantic Scholar. - AI2 has scaled up the Semantic Scholar search engine to include biomedical research. - In 2018, AI2 joined forces with Microsoft Research to enhance search tools for scientific studies. - GeekWire has reported on AI2's collaboration with Semantic Scholar. - The GeekWire article from 2018 mentions that AI2 hired a machine learning leader from Amazon Alexa. Impact and Expansion of Semantic Scholar - Semantic Scholar has a significant impact on the field of scientific research. - It aims to improve search and discoverability of scientific studies. - The search engine has been expanded to encompass a wide range of research topics. - GeekWire has reported on the expansion of Semantic Scholar's search tools. - Semantic Scholar has received recognition and partnership from over 500 publishers. Relevance and Usage of Semantic Scholar - Semantic Scholar is widely used by researchers and scholars in the scientific community. - It offers an extensive collection of scientific papers for users to search and explore. - The search engine's coverage includes software engineering and biomedical research. - Semantic Scholar has received positive feedback for its search capabilities and discoverability. - The addition of new publisher partnerships has significantly increased the number of papers available.