LYNX (Linked Knowledge Network Explorer) is a semantic mapping and visualization platform designed to transform knowledge exploration through an immersive 3D galaxy metaphor. The system integrates semantic embeddings, graph theory, and 3D rendering to reveal conceptual relationships across diverse knowledge domains. LYNX processes data from sources such as Wikipedia and arXiv, generating 384-dimensional embeddings via Sentence-BERT to compute semantic similarity between concepts. The resulting graph is visualized in an interactive WebGL environment that supports semantic search, dynamic navigation, and progressive Level-of-Detail rendering for scalable performance. The platform demonstrates sub-200 ms search latency and sustained 60 FPS visualization for datasets exceeding 10,000 concepts. This paper details the architecture, implementation, and evaluation of the LYNX system, showcasing its potential applications in research, education, and information discovery.