The invention discloses a semantic approximate query method for an
RDF knowledge map. The offline stage of the invention comprises the following steps: firstly, the
RDF knowledge map is divided into
RDF knowledge maps according to the semantic locality characteristics of entities and predicates of the RDF knowledge map, and the divided knowledge maps are generated into trainable
text corpus; secondly, context-sensitive
semantic learning is performed on the
text corpus using the text embedding model, and the semantic vectors of entities and predicates are obtained. In the on-line phase: firstly, the
syntax of
SPARQL query submitted by users is analyzed, and the
semantics of the predicates is extended; secondly, an approximate query based on predicate
semantic similarity is carried out froma given entity, and the semantic approximate query results are obtained. The method utilizes semantic locality features to carry out context-sensitive
semantic learning on the RDF knowledge map, thereby supporting
fuzzy query application of the RDF knowledge map, and returning approximate query results satisfying user query intent in real time.