Abstract
To solve the problems such as low level automation and poor adaptability of current entity recognition methods,a Deep Web entity recognition method based on Back Propagation(BP) neural network was proposed in this paper.The method divided the entities into blocks first,then used the similarity of semantic blocks as the input of BP neural network,lastly obtained a correct entity recognition model by training which was based on the autonomic learning ability of BP neural network.It can achieve entity recognition automation in heterogeneous data sources.The experimental results show that the application of the method can not only reduce manual interventions,but also improve the efficiency and the accuracy rate of entity recognition.
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