Semantic Scholar Overview and Features - Semantic Scholar provides a one-sentence summary of scientific literature. - It aims to address the challenge of reading numerous titles and lengthy abstracts on mobile devices. - The project uses artificial intelligence to generate the essence of a paper through an abstractive technique. - It combines machine learning, natural language processing, and machine vision to add semantic analysis to citation analysis. - Research Feeds, an AI-powered feature, recommends the latest research to help scholars stay up to date. - Semantic Reader is an augmented reader that revolutionizes scientific reading by making it more accessible and contextual. - It provides in-line citation cards with TLDR summaries and skimming highlights to help users digest information faster. - Semantic Scholar is designed to highlight the most important and influential elements of a paper. - The AI technology identifies hidden connections and links between research topics. - It exploits graph structures, including the Microsoft Academic Knowledge Graph and Springer Nature's SciGraph. - Semantic Scholar does not search for material behind a paywall and is free to use.

Number of Users and Publications - The Semantic Scholar corpus includes more than 40 million papers from computer science and biomedicine. - The number of included papers metadata has grown to more than 173 million, including the Microsoft Academic Graph records. - A partnership with the University of Chicago Press Journals made all articles published under the 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.

Comparison with Other Search Engines - A study found that for papers cited by secondary studies in computer science, Semantic Scholar and Google Scholar had comparable coverage. - It uses AI and cannot distinguish between reviews of books and the books themselves. - It struggles to distinguish between authors with common names due to its use of science standards for author identification. - The assigned field for papers is not always clearly distinguished, leading to issues like listing History for Literature papers.

Related Concepts and Resources - Citation analysis examines the frequency, patterns, and graphs of citations in documents. - Citation index is an index of citations between publications. - Knowledge extraction involves creating knowledge from structured and unstructured sources. - There is a list of academic databases and search engines for further exploration. - Scientometrics is the study of measuring and analyzing science, technology, and innovation.

Semantic Scholar Partnerships and Expansion - Semantic Scholar has coverage of over 500 publishers, including the University of Chicago Press. - In 2020, Semantic Scholar added 25 million scientific papers through new publisher partnerships. - AI2, the Allen Institute for Artificial Intelligence, expanded Semantic Scholar to include biomedical research. - AI2 collaborated with Microsoft Research to upgrade search tools for scientific studies. - Semantic Scholar has gained recognition and usage in the scientific community and plays a crucial role in improving the accessibility and visibility of scientific research.