Recent Advancements in Search-Engine Algorithms for Efficiency, Privacy and Security
Jeremy Wolfe, Clark Pfohl, Hariharan Subramanian, J. Sukarno Mertoguno, Michail S. Alexiou · 2024
This survey explores the technical aspects of how companies implement their search engines to minimize costs. In addition, by examining the algorithms and techniques employed by various companies, the current paper seeks to understand the strategies used for analyzing data and delivering personalized results, while preserving the user's privacy. In particular, the study scrutinizes specific algorithmic choices, architectures, efficiency, security measures, and vulnerabilities. It identifies nuances in search result personalization and evaluates diverse algorithms to discern best practices in search engine optimization. Additionally, the paper investigates how emerging AI and machine learning technologies can innovate current search engine capabilities. Through the aforementioned theoretical analysis, the current survey aims to highlight what renders these systems efficient, secure, or susceptible to potential vulnerabilities, thus, laying the groundwork for future research on the development of robust and resilient search-engine architectures.