Generative AI for Learning and Research

You may notice that some AI research tools, like Elicit and Connected Papers, utilize data from Semantic Scholar as part of their sources. Have you ever wondered what this platform is?

Semantic Scholar, launched in 2015, is an AI-powered academic search engine that aims at providing researchers with more efficient and insightful ways to discover and understand scientific literature. Some key features include:

• AI-Driven Search: maximizes advanced natural language processing and machine algorithms to understand the content and context of academic papers.
• Citation Analysis: identify the context in which the cited publications are used. The Highly Influential Citation reflects the significance of the cited publication on the citing publication, facilitating comprehensiveness of the relationships between publications.
• Semantic Reader: an augmented PDF reader is available for reading the full text with AI-generated skimming highlights that pinpoint key aspects of the publication. You will also find the "Ask This Paper" function available, which is designed to answer questions about the specific publication you are reading.

References:

• Semantic Scholar: Exploring Research Literature with “Meanings.” (n.d.). https://library.hkust.edu.hk/sc/semantic-scholar/
• Semantic Scholar | Frequently asked questions. (n.d.). https://www.semanticscholar.org/faq
• Semantic Scholar Review: Features, Benefits & Uses Cases (2024) — Otio blog. (n.d.). https://otio.ai/blog/semantic-scholar#:~:text=your%20research%20endeavors.-,7%20Best%20Alternatives%20To%20Semantic%20Scholar,-1.%20Otio%3A%20The

While Semantic Scholar offers a new way of searching literature, Google Scholar remains the fundamental platform for students and researchers to locate useful academic materials. To obtain a thorough search, you may benefit from using both tools to leverage their respective strengths. 

Below is a table comparing the major functionalities of Semantic Scholar and Google Scholar: