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- W4225685968 abstract "Now the Internet is flooded with a large amount of undesirable information, which harms the network ecological environment and it should be cleared. At present, it mainly relies on manual methods, and there are problems such as slow and incomplete identification in undesirable text recognition. In order to solve the problems, this paper proposes a method of undesirable text recognition based on deep learning and knowledge graph. It combines the undesirable information knowledge graph and the context relationship, together with the user's search intention, extracts the vector and input by the deep learning neural network to obtain the target result. Experiment shows that compared with other traditional methods, this method can achieve better classification result and improve the accuracy of web undesirable text recognition for different topics." @default.
- W4225685968 created "2022-05-05" @default.
- W4225685968 creator A5017296972 @default.
- W4225685968 date "2021-11-12" @default.
- W4225685968 modified "2023-10-01" @default.
- W4225685968 title "Research on Method of Undesirable Text Recognition based on Deep Learning and Knowledge Graph" @default.
- W4225685968 doi "https://doi.org/10.1145/3503928.3503941" @default.
- W4225685968 hasPublicationYear "2021" @default.
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