New online search engine targeted to academics
DOI: 10.1063/PT.5.029342
MIT Technology Review : “Cut through the clutter” is the catchphrase of Semantic Scholar , a new online tool that uses machine-learning techniques to look for ideas, read graphs, and glean other useful information from the millions of computer science papers that have been published. Although other academic search engines exist, such as Google Scholar and PubMed, most rely on keywords, publication dates, and other basic metadata. Semantic Scholar, however, uses algorithms and other artificial intelligence software to go beyond simple searches to extract specific concepts. Oren Etzioni, executive director of the Allen Institute for Artificial Intelligence, which developed Semantic Scholar, says that with the large number of papers published each year, researchers need a way to quickly and efficiently find the information relevant to them.