Applying Semantic Feature Fusion for Enhanced Genetic Data Retrieval in Biotechnology

Abstract

To optimize biotechnological data management, this study adapts an intelligent retrieval method initially developed for a folk music database, applying semantic feature fusion. The approach analyzes the construction and challenges of databases, utilizing AI-driven semantic understanding to enhance the accuracy and efficiency of genetic data retrieval. By synthesizing complex data characteristics, this method demonstrates significant improvements in accessing and processing genetic databases, supporting more effective and precise biotechnological research.