elimination and integration problems for Deep Web database
make the Deep Web database entity query performance with optimization
the database entity recognition intelligent semantic query method based on autocorrelation characteristics was proposed.The query model consisted of text matching model
semantic correlation characteristic analysis model and the statistical model
and semantic correlation feature extraction algorithm was proposed.The semantic information constraint rule was defined for optimal approximation database entity recognition results.The semantic correlation characteristics were used to establish the surface correlation knowledge base
the correction
elimination
integration was realized in the data query.The mathematical derivation proves that the stability of the algorithm
and simulation results show that algorithm can consider
text feature
semantic correlation feature and constraint rules
the accuracy and completeness of data query increased significantly and effectively.