Summary
This document is a guide that outlines the evolution and current state of AI-based search platforms in the context of academic and scientific research. It describes how these platforms have emerged as a response to the automation trends initiated during the Industrial Revolution, where machines began to replace human labor. The guide details various AI-based search engines, including Google Scholar, Microsoft Academic, Semantic Scholar, Yewno, Sparrho, and UNSILO, highlighting their functionalities and unique features. For instance, Yewno utilizes graphic representations to connect different sources, while Sparrho personalizes research recommendations based on user interactions. The document also discusses the competitive landscape among key players like Google, Microsoft, and AI2, as well as the future goals of these platforms, which focus on personalization, specificity, efficiency, and relevancy in research results. The guide concludes by addressing the dual concepts of globalization and personalization in research navigation, emphasizing the need for tailored content curation in a globalized context.
