Semantic Search

Semantic search aims to improve information retrieval by understanding the meaning and context of search queries, rather than relying solely on keyword matches. Current research focuses on integrating large language models (LLMs) with knowledge graphs and various embedding techniques (e.g., bi-encoders, cross-encoders) to enhance accuracy and efficiency, often addressing challenges like class imbalance and ambiguity in query interpretation. This field is significant for improving the usability of large datasets across diverse domains, from scholarly publications and e-commerce to specialized knowledge bases in fields like materials science and legal research.