Semantic Scholar

Table of Contents

Developed at the Allen Institute for , Semantic Scholar is a search engine for academic papers supported by artificial Semantic Scholar intelligence that was made available to the public in November 2024.

It generates summaries of academic publications by utilising developments in natural language processing.

The Semantic Scholar team is currently conducting research on artificial intelligence applications in information retrieval, machine learning, natural language processing, and human-computer interaction.

Semantic Scholar

Initially, Semantic Scholar was a database pertaining to computer science, neuroscience, and geoscience. Nonetheless, the system started adding biomedical literature to its corpus in 2017. They now contain publications from every branch of research as of November 2021.

A semantic scholar summarizes scientific literature into a single sentence. Addressing the difficulty of reading many titles and lengthy summaries on mobile devices was one of its objectives. gadgets. Additionally, since only half of the three million scientific papers published each year are ever read, it aims to make sure that readers can access this body of work.

The essence of a document is generated by artificial intelligence using an “abstractive” technique. The project extracts pertinent figures, tables, entities, and places from publications and adds a semantic analysis layer to the conventional citation analysis techniques using a blend of machine learning, natural language processing, and machine vision.

Semantic Scholar, as opposed to Google Scholar and PubMed, is intended to draw attention to the most significant and impactful parts of a publication. The purpose of AI technology is to find unnoticed relationships and connections between research areas.

similar to the previously mentioned In addition to using search engines, makes use of graph structures, such as the Corpus, Microsoft Academic Knowledge Graph, and Springer Nature’s SciGraph.

The Semantic Scholar Corpus ID, also known as the S2CID is a special number that is assigned to each paper housed by . Here’s an example of an entry

FAQ

What is Semantic Scholar?

In order to assist Scholars in finding pertinent research, Semantic Scholar leverages cutting-edge AI and engineering to comprehend the semantics of scientific publications.

Semantic search: what is it?

Both of these search engines used semantic searching, which focuses on interpreting users’ possible meanings rather than precisely returning results based on the search phrases entered. This differs from standard literal searching.

In what ways do search engines support scientific research and innovation?

In an interview with Dan Weld, Chief Scientist of Semantic Scholar, Nature learned how search engines facilitate scientific discovery and innovation by facilitating the process of discovering connections among a vast body of scientific literature. All academics may use open materials and AI-powered research tools for free at Semantic Scholar.

Semantic Scholar Academic Graph (s2ag): What is it?

The Semantic Scholar Academic Graph (S2AG) Dataset and APIs offer easily navigable JSON archives containing records of research publications published across all subjects.

Reference by

https://www.semanticscholar.org/

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