Graph Question Answering

Graph Question Answering is a method that combines graph-structured data with natural language processing techniques. It aims to parse natural language questions posed by users and use the relationships and attributes in graph data for reasoning and querying, providing accurate and efficient answers. This technology can deeply explore the intrinsic connections within graph data, enhancing the precision and efficiency of information retrieval. It is widely applied in knowledge graphs, intelligent recommendations, semantic search, and other fields, possessing significant application value.