Semantic retrieval on art museum database system


We discuss a semantic retrieval method on an art museum database system ArtFinder. It is characteristic of the semantic retrieval to use the semantics of art works as keys. By using this function, the user can find art works which he/she imagines. There are three kinds of knowledge in ArtFinder: art work knowledge, art knowledge and general knowledge. The art work knowledge is the meanings of art works. The art knowledge is the expert knowledge about art. The general knowledge is the common sense in daily life about the objects depicted in art works. Using these knowledge, the user can understand the interpretations of art works and find other art works which are resemble in the meaning.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL